'I lose my cool only when someone crosses the limit.''But these people have become really smart.''They know they will be here for a long time if I lose my cool on them.'

Some #BottleCapChallenge stunts are very funny.

Sonam Kapoor likes to mix and match movie genres but picks comedy as her favourite.

'My life hasn't changed much, in terms of how I travel and work since I got married. Nick and I are both work-oriented and have a lot of drive and ambition. But two countries are a part of it, so it takes a lot of flights, a lot of beating jet lag, forgetting to eat, not getting enough time to sleep...'

It was a warm family affair, where Padmini Kolhapure and Ravi Kishan launched the careers of their respective children.

The self-described entrepreneur had surprised all by joining Nirav Modi four years ago

Sorrell's exit would have been a big deal at any point, but the manner of his departure has amplified the attention

Dewey Library - PS3567.U3618 T35 2019

Dewey Library - PS3573.I45575 A6 2019

Hayden Library - PS3623.I66425 I5 2019

Hayden Library - PS3626.A6276 A6 2019

Dewey Library - PS3619.C32575 A6 2018

Dewey Library - PS3515.U789 A6 2020b

Dewey Library - PS228.E95 C43 2019

Dewey Library - PS3545.R815 Z798 2018

Un film de Julie Bertuccelli

César de la meilleure première œuvre 2004
Grand prix de la semaine de la critique Festival de Cannes 2003
Grand Prix du meilleur scénario 2001

À travers l’histoire d’un mensonge d’amour se dessine le portait délicat de trois femmes de trois générations dans la Géorgie d’aujourd’hui.

LE FILM

En Géorgie trois femmes de trois générations vivent seules dans un petit appartement à Tbilissi. La grand-mère, Eka, vieille dame délicieuse, francophile et légèrement nostalgique de l’époque stalinienne, où l’électricité était plus fiable, Marina, sa fille et sœur d’Otar, diplômée, gagne modestement et tristement la vie de la famille. Enfin, Ada, la petite-fille, interprète du russe au français, rêverait d’être à Paris, elle aussi… Otar, l’homme de la famille, le fils, le frère et l’oncle, médecin, a quitté le pays pour aller travailler en France et tenter d’obtenir une vie meilleure. Il téléphone de temps à autre et écrit en racontant Montmartre, Saint-Germain-des-Prés… Eka, revit et se transfigure à chaque missive, à chaque appel.

Un jour, Marina et Ada apprennent qu’Otar est mort, tombé de l’échafaudage où il travaillait. Epouvantées, anéanties, elles se refusent à en parler à la grand-mère et décident de lui faire croire qu’il est toujours vivant. Ada écrit donc des lettres qu’elle invente en imitant l’écriture de son oncle, tandis qu’elle et sa mère se serrent la ceinture pour faire croire que rien n’a changé.

Finalement la grand-mère n’y tenant plus, décide de partir pour Paris avec ses fille et petite-fille et de revoir Otar.

Une comédie douce et amère, un film poignant où le dit et le non-dit créent une trame délicate, intense, subtile. Trois personnalités de femmes sublimes ; un peu comme la même femme à trois âges de la vie… Un « film-peinture de la vie en Géorgie » en plein chaos post soviétique aussi, filmé par une jeune réalisatrice, Julie Bertuccelli, au talent prometteur… à découvrir !!!

LA REALISATRICE

Julie BERTUCCELLI, documentaliste, a été assistante de Krzysztof Kieslowski, Bertrand Tavernier, Emmanuel Finkiel, Rithy Panh, Otar Iosselliani grâce auquel elle a découvert la Géorgie. Depuis qu’Otar est parti est son premier long métrage de fiction.

« J’ai travaillé pendant six mois en Géorgie avec Iosseliani et je suis tombée amoureuse de ce pays, au carrefour de l’Europe et de l’Asie, au confluent des cultures et des civilisations. Les gens y sont chaleureux, attachants, truculents. Les Géorgiens sont des poètes, des peintres, des danseurs.

Pour ce film, je suis partie d’une histoire authentique racontée par une amie géorgienne. Elle avait le mérite d’être à la fois romanesque et vraie. Avec Bernard Renucci, mon co-scénariste, nous nous sommes très vite éloignés de la réalité. Ce qui nous intéressait, c’était avant tout d’explorer les relations entre les trois femmes obligées d’habiter ensemble. En Géorgie, il n’y a pas de maison de retraite. Les vieux habitent donc avec les enfants et les petits enfants.

Nous avons voulu aussi montrer comment elles ont vécu le passage entre le communisme et le capitalisme sauvage d’aujourd’hui. Quels sont à présent leurs désirs, leurs espoirs, leur devenir ? »

LES COMEDIENNES

Les trois comédiennes donnent aux personnages une authenticité et une sensibilité merveilleuses. Elles sont mises en valeur par la douceur des couleurs et l’atmosphère de tendre rêverie donnée par la caméra ; elles dégagent une grande harmonie et révèlent la profondeur subtile de ces trois femmes unies par le destin et si différentes.

Dinara Droukarova, joue ADA, la petite fille, Nino Khomassouridze, MARINA, la mère et Esther Gorintin, EKA, la grand-mère. Cette dernière, âgée de 90 ans, avait déjà fait forte impression dans le film Voyages d’Emmanuel Finkiel.

LE DVD VIDEO

Compléments

• 10 scènes coupées (25 minutes) commentée par la réalisatrice
• Tbilissi impressions : montage photos
• Making of (40 minutes) : la préparation du film, le premier jour de tournage, les puces, le parc d’attractions

Caractéristiques techniques

Zone 2, pal, DVD 9, 16 compatible 4/3, son dolby digital 5.1 et stéréo, 98 minutes, couleur, film en VOST.

Online Resource

Hayden Library - QA329.4.G4513 2019

Hayden Library - QA171.L63 2018

Browsery DVD MT100.S968.V3 2016

Browsery DVD V195 pas

Browsery DVD C4724 hom

Browsery DVD T782 sy1

Browsery DVD G463 ein a

Browsery DVD ML422.K37 H473 2016

Autor: Hofmann, Heinrich, 1842-1902
Erschienen 1873
BSB-Signatur 4 Mus.pr. 46076

URN: urn:nbn:de:bvb:12-bsb11149056-0
URL: http://reader.digitale-sammlungen.de/de/fs1/object/display/bsb11149056_00001.html/

Autor: Raff, Joseph Joachim, 1822-1882
Erschienen 1868
BSB-Signatur 4 Mus.pr. 44821

URN: urn:nbn:de:bvb:12-bsb11148829-3
URL: http://reader.digitale-sammlungen.de/de/fs1/object/display/bsb11148829_00001.html/

Autor: Pott, August, 1806-1883
Erschienen 1842
BSB-Signatur 4 Mus.pr. 44424-1/2

URN: urn:nbn:de:bvb:12-bsb11148799-0
URL: http://reader.digitale-sammlungen.de/de/fs1/object/display/bsb11148799_00001.html/

Autor: Pott, August, 1806-1883
Erschienen 1842
BSB-Signatur 4 Mus.pr. 44424-1/2

URN: urn:nbn:de:bvb:12-bsb11148800-9
URL: http://reader.digitale-sammlungen.de/de/fs1/object/display/bsb11148800_00001.html/

[U.K.] : Artifical Eye, [2014]

[U.S.A.] : Cohen Media Group, [2019]

Westerner

Gibson, David, 1957- author

Once upon a time, we relied on browsers to handle caching for us; as developers in those days, we had very little control. But then came Progressive Web Apps (PWAs), Service Workers, and the Cache API—and suddenly we have expansive power over what gets put in the cache and how it gets put there. We can now cache everything we want to… and therein lies a potential problem.

Media files—especially images—make up the bulk of average page weight these days, and it’s getting worse. In order to improve performance, it’s tempting to cache as much of this content as possible, but should we? In most cases, no. Even with all this newfangled technology at our fingertips, great performance still hinges on a simple rule: request only what you need and make each request as small as possible.

To provide the best possible experience for our users without abusing their network connection or their hard drive, it’s time to put a spin on some classic best practices, experiment with media caching strategies, and play around with a few Cache API tricks that Service Workers have hidden up their sleeves.

Best intentions

All those lessons we learned optimizing web pages for dial-up became super-useful again when mobile took off, and they continue to be applicable in the work we do for a global audience today. Unreliable or high latency network connections are still the norm in many parts of the world, reminding us that it’s never safe to assume a technical baseline lifts evenly or in sync with its corresponding cutting edge. And that’s the thing about performance best practices: history has borne out that approaches that are good for performance now will continue being good for performance in the future.

Before the advent of Service Workers, we could provide some instructions to browsers with respect to how long they should cache a particular resource, but that was about it. Documents and assets downloaded to a user’s machine would be dropped into a directory on their hard drive. When the browser assembled a request for a particular document or asset, it would peek in the cache first to see if it already had what it needed to possibly avoid hitting the network.

We have considerably more control over network requests and the cache these days, but that doesn’t excuse us from being thoughtful about the resources on our web pages.

Request only what you need

As I mentioned, the web today is lousy with media. Images and videos have become a dominant means of communication. They may convert well when it comes to sales and marketing, but they are hardly performant when it comes to download and rendering speed. With this in mind, each and every image (and video, etc.) should have to fight for its place on the page. 

A few years back, a recipe of mine was included in a newspaper story on cooking with spirits (alcohol, not ghosts). I don’t subscribe to the print version of that paper, so when the article came out I went to the site to take a look at how it turned out. During a recent redesign, the site had decided to load all articles into a nearly full-screen modal viewbox layered on top of their homepage. This meant requesting the article required requests for all of the assets associated with the article page plus all the contents and assets for the homepage. Oh, and the homepage had video ads—plural. And, yes, they auto-played.

I popped open DevTools and discovered the page had blown past 15 MB in page weight. Tim Kadlec had recently launched What Does My Site Cost?, so I decided to check out the damage. Turns out that the actual cost to view that page for the average US-based user was more than the cost of the print version of that day’s newspaper. That’s just messed up.

Sure, I could blame the folks who built the site for doing their readers such a disservice, but the reality is that none of us go to work with the goal of worsening our users’ experiences. This could happen to any of us. We could spend days scrutinizing the performance of a page only to have some committee decide to set that carefully crafted page atop a Times Square of auto-playing video ads. Imagine how much worse things would be if we were stacking two abysmally-performing pages on top of each other!

Media can be great for drawing attention when competition is high (e.g., on the homepage of a newspaper), but when you want readers to focus on a single task (e.g., reading the actual article), its value can drop from important to “nice to have.” Yes, studies have shown that images excel at drawing eyeballs, but once a visitor is on the article page, no one cares; we’re just making it take longer to download and more expensive to access. The situation only gets worse as we shove more media into the page. 

We must do everything in our power to reduce the weight of our pages, so avoid requests for things that don’t add value. For starters, if you’re writing an article about a data breach, resist the urge to include that ridiculous stock photo of some random dude in a hoodie typing on a computer in a very dark room.

Request the smallest file you can

Now that we’ve taken stock of what we do need to include, we must ask ourselves a critical question: How can we deliver it in the fastest way possible? This can be as simple as choosing the most appropriate image format for the content presented (and optimizing the heck out of it) or as complex as recreating assets entirely (for example, if switching from raster to vector imagery would be more efficient).

Offer alternate formats

When it comes to image formats, we don’t have to choose between performance and reach anymore. We can provide multiple options and let the browser decide which one to use, based on what it can handle.

You can accomplish this by offering multiple sources within a picture or video element. Start by creating multiple formats of the media asset. For example, with WebP and JPG, it’s likely that the WebP will have a smaller file size than the JPG (but check to make sure). With those alternate sources, you can drop them into a picture like this:

<picture>
  <source srcset="my.webp" type="image/webp">
  <img src="my.jpg" alt="Descriptive text about the picture.">
</picture>

Browsers that recognize the picture element will check the source element before making a decision about which image to request. If the browser supports the MIME type “image/webp,” it will kick off a request for the WebP format image. If not (or if the browser doesn’t recognize picture), it will request the JPG. 

The nice thing about this approach is that you’re serving the smallest image possible to the user without having to resort to any sort of JavaScript hackery.

You can take the same approach with video files:

<video controls>
  <source src="my.webm" type="video/webm">
  <source src="my.mp4" type="video/mp4">
  <p>Your browser doesn’t support native video playback,
    but you can <a href="my.mp4" download>download</a>
    this video instead.</p>
</video>

Browsers that support WebM will request the first source, whereas browsers that don’t—but do understand MP4 videos—will request the second one. Browsers that don’t support the video element will fall back to the paragraph about downloading the file.

The order of your source elements matters. Browsers will choose the first usable source, so if you specify an optimized alternative format after a more widely compatible one, the alternative format may never get picked up.  

Depending on your situation, you might consider bypassing this markup-based approach and handle things on the server instead. For example, if a JPG is being requested and the browser supports WebP (which is indicated in the Accept header), there’s nothing stopping you from replying with a WebP version of the resource. In fact, some CDN services—Cloudinary, for instance—come with this sort of functionality right out of the box.

Offer different sizes

Formats aside, you may want to deliver alternate image sizes optimized for the current size of the browser’s viewport. After all, there’s no point loading an image that’s 3–4 times larger than the screen rendering it; that’s just wasting bandwidth. This is where responsive images come in.

Here’s an example:

<img src="medium.jpg"
  srcset="small.jpg 256w,
    medium.jpg 512w,
    large.jpg 1024w"
  sizes="(min-width: 30em) 30em, 100vw"
  alt="Descriptive text about the picture.">

There’s a lot going on in this super-charged img element, so I’ll break it down:

• This img offers three size options for a given JPG: 256 px wide (small.jpg), 512 px wide (medium.jpg), and 1024 px wide (large.jpg). These are provided in the srcset attribute with corresponding width descriptors.
• The src defines a default image source, which acts as a fallback for browsers that don’t support srcset. Your choice for the default image will likely depend on the context and general usage patterns. Often I’d recommend the smallest image be the default, but if the majority of your traffic is on older desktop browsers, you might want to go with the medium-sized image.
• The sizes attribute is a presentational hint that informs the browser how the image will be rendered in different scenarios (its extrinsic size) once CSS has been applied. This particular example says that the image will be the full width of the viewport (100vw) until the viewport reaches 30 em in width (min-width: 30em), at which point the image will be 30 em wide. You can make the sizes value as complicated or as simple as you want; omitting it causes browsers to use the default value of 100vw.

You can even combine this approach with alternate formats and crops within a single picture. ????

All of this is to say that you have a number of tools at your disposal for delivering fast-loading media, so use them!

Defer requests (when possible)

Years ago, Internet Explorer 11 introduced a new attribute that enabled developers to de-prioritize specific img elements to speed up page rendering: lazyload. That attribute never went anywhere, standards-wise, but it was a solid attempt to defer image loading until images are in view (or close to it) without having to involve JavaScript.

There have been countless JavaScript-based implementations of lazy loading images since then, but recently Google also took a stab at a more declarative approach, using a different attribute: loading.

The loading attribute supports three values (“auto,” “lazy,” and “eager”) to define how a resource should be brought in. For our purposes, the “lazy” value is the most interesting because it defers loading the resource until it reaches a calculated distance from the viewport.

Adding that into the mix…

<img src="medium.jpg"
  srcset="small.jpg 256w,
    medium.jpg 512w,
    large.jpg 1024w"
  sizes="(min-width: 30em) 30em, 100vw"
  loading="lazy"
  alt="Descriptive text about the picture.">

This attribute offers a bit of a performance boost in Chromium-based browsers. Hopefully it will become a standard and get picked up by other browsers in the future, but in the meantime there’s no harm in including it because browsers that don’t understand the attribute will simply ignore it.

This approach complements a media prioritization strategy really well, but before I get to that, I want to take a closer look at Service Workers.

Manipulate requests in a Service Worker

Service Workers are a special type of Web Worker with the ability to intercept, modify, and respond to all network requests via the Fetch API. They also have access to the Cache API, as well as other asynchronous client-side data stores like IndexedDB for resource storage.

When a Service Worker is installed, you can hook into that event and prime the cache with resources you want to use later. Many folks use this opportunity to squirrel away copies of global assets, including styles, scripts, logos, and the like, but you can also use it to cache images for use when network requests fail.

Keep a fallback image in your back pocket

Assuming you want to use a fallback in more than one networking recipe, you can set up a named function that will respond with that resource:

function respondWithFallbackImage() {
  return caches.match( "/i/fallbacks/offline.svg" );
}

Then, within a fetch event handler, you can use that function to provide that fallback image when requests for images fail at the network:

self.addEventListener( "fetch", event => {
  const request = event.request;
  if ( request.headers.get("Accept").includes("image") ) {
    event.respondWith(
      return fetch( request, { mode: 'no-cors' } )
        .then( response => {
          return response;
        })
        .catch(
          respondWithFallbackImage
        );
    );
  }
});

When the network is available, users get the expected behavior:

But when the network is interrupted, images will be swapped automatically for a fallback, and the user experience is still acceptable:

On the surface, this approach may not seem all that helpful in terms of performance since you’ve essentially added an additional image download into the mix. With this system in place, however, some pretty amazing opportunities open up to you.

Respect a user’s choice to save data

Some users reduce their data consumption by entering a “lite” mode or turning on a “data saver” feature. When this happens, browsers will often send a Save-Data header with their network requests. 

Within your Service Worker, you can look for this header and adjust your responses accordingly. First, you look for the header:

let save_data = false;
if ( 'connection' in navigator ) {
  save_data = navigator.connection.saveData;
}

Then, within your fetch handler for images, you might choose to preemptively respond with the fallback image instead of going to the network at all:

self.addEventListener( "fetch", event => {
  const request = event.request;
  if ( request.headers.get("Accept").includes("image") ) {
    event.respondWith(
      if ( save_data ) {
        return respondWithFallbackImage();
      }
      // code you saw previously
    );
  }
});

You could even take this a step further and tune respondWithFallbackImage() to provide alternate images based on what the original request was for. To do that you’d define several fallbacks globally in the Service Worker:

const fallback_avatar = "/i/fallbacks/avatar.svg",
      fallback_image = "/i/fallbacks/image.svg";

Both of those files should then be cached during the Service Worker install event:

return cache.addAll( [
  fallback_avatar,
  fallback_image
]);

Finally, within respondWithFallbackImage() you could serve up the appropriate image based on the URL being fetched. In my site, the avatars are pulled from Webmention.io, so I test for that.

function respondWithFallbackImage( url ) {
  const image = avatars.test( /webmention.io/ ) ? fallback_avatar
                                                 : fallback_image;
  return caches.match( image );
}

With that change, I’ll need to update the fetch handler to pass in request.url as an argument to respondWithFallbackImage(). Once that’s done, when the network gets interrupted I end up seeing something like this:

Next, we need to establish some general guidelines for handling media assets—based on the situation, of course.

The caching strategy: prioritize certain media

In my experience, media—especially images—on the web tend to fall into three categories of necessity. At one end of the spectrum are elements that don’t add meaningful value. At the other end of the spectrum are critical assets that do add value, such as charts and graphs that are essential to understanding the surrounding content. Somewhere in the middle are what I would call “nice-to-have” media. They do add value to the core experience of a page but are not critical to understanding the content.

If you consider your media with this division in mind, you can establish some general guidelines for handling each, based on the situation. In other words, a caching strategy.

When it comes to disambiguating the critical from the nice-to-have, it’s helpful to have those resources organized into separate directories (or similar). That way we can add some logic into the Service Worker that can help it decide which is which. For example, on my own personal site, critical images are either self-hosted or come from the website for my book. Knowing that, I can write regular expressions that match those domains:

const high_priority = [
    /aaron-gustafson.com/,
    /adaptivewebdesign.info/
  ];

With that high_priority variable defined, I can create a function that will let me know if a given image request (for example) is a high priority request or not:

function isHighPriority( url ) {
  // how many high priority links are we dealing with?
  let i = high_priority.length;
  // loop through each
  while ( i-- ) {
    // does the request URL match this regular expression?
    if ( high_priority[i].test( url ) ) {
      // yes, it’s a high priority request
      return true;
    }
  }
  // no matches, not high priority
  return false;
}

Adding support for prioritizing media requests only requires adding a new conditional into the fetch event handler, like we did with Save-Data. Your specific recipe for network and cache handling will likely differ, but here was how I chose to mix in this logic within image requests:

// Check the cache first
  // Return the cached image if we have one
  // If the image is not in the cache, continue

// Is this image high priority?
if ( isHighPriority( url ) ) {

  // Fetch the image
    // If the fetch succeeds, save a copy in the cache
    // If not, respond with an "offline" placeholder

// Not high priority
} else {

  // Should I save data?
  if ( save_data ) {

    // Respond with a "saving data" placeholder

  // Not saving data
  } else {

    // Fetch the image
      // If the fetch succeeds, save a copy in the cache
      // If not, respond with an "offline" placeholder
  }
}

We can apply this prioritized approach to many kinds of assets. We could even use it to control which pages are served cache-first vs. network-first.

Keep the cache tidy

The  ability to control which resources are cached to disk is a huge opportunity, but it also carries with it an equally huge responsibility not to abuse it.

Every caching strategy is likely to differ, at least a little bit. If we’re publishing a book online, for instance, it might make sense to cache all of the chapters, images, etc. for offline viewing. There’s a fixed amount of content and—assuming there aren’t a ton of heavy images and videos—users will benefit from not having to download each chapter separately.

On a news site, however, caching every article and photo will quickly fill up our users’ hard drives. If a site offers an indeterminate number of pages and assets, it’s critical to have a caching strategy that puts hard limits on how many resources we’re caching to disk. 

One way to do this is to create several different blocks associated with caching different forms of content. The more ephemeral content caches can have strict limits around how many items can be stored. Sure, we’ll still be bound to the storage limits of the device, but do we really want our website to take up 2 GB of someone’s hard drive?

Here’s an example, again from my own site:

const sw_caches = {
  static: {
    name: `${version}static`
  },
  images: {
    name: `${version}images`,
    limit: 75
  },
  pages: {
    name: `${version}pages`,
    limit: 5
  },
  other: {
    name: `${version}other`,
    limit: 50
  }
}

Here I’ve defined several caches, each with a name used for addressing it in the Cache API and a version prefix. The version is defined elsewhere in the Service Worker, and allows me to purge all caches at once if necessary.

With the exception of the static cache, which is used for static assets, every cache has a limit to the number of items that may be stored. I only cache the most recent 5 pages someone has visited, for instance. Images are limited to the most recent 75, and so on. This is an approach that Jeremy Keith outlines in his fantastic book Going Offline (which you should really read if you haven’t already—here’s a sample).

With these cache definitions in place, I can clean up my caches periodically and prune the oldest items. Here’s Jeremy’s recommended code for this approach:

function trimCache(cacheName, maxItems) {
  // Open the cache
  caches.open(cacheName)
  .then( cache => {
    // Get the keys and count them
    cache.keys()
    .then(keys => {
      // Do we have more than we should?
      if (keys.length > maxItems) {
        // Delete the oldest item and run trim again
        cache.delete(keys[0])
        .then( () => {
          trimCache(cacheName, maxItems)
        });
      }
    });
  });
}

We can trigger this code to run whenever a new page loads. By running it in the Service Worker, it runs in a separate thread and won’t drag down the site’s responsiveness. We trigger it by posting a message (using postMessage()) to the Service Worker from the main JavaScript thread:

// First check to see if you have an active service worker
if ( navigator.serviceWorker.controller ) {
  // Then add an event listener
  window.addEventListener( "load", function(){
    // Tell the service worker to clean up
    navigator.serviceWorker.controller.postMessage( "clean up" );
  });
}

The final step in wiring it all up is setting up the Service Worker to receive the message:

addEventListener("message", messageEvent => {
  if (messageEvent.data == "clean up") {
    // loop though the caches
    for ( let key in sw_caches ) {
      // if the cache has a limit
      if ( sw_caches[key].limit !== undefined ) {
        // trim it to that limit
        trimCache( sw_caches[key].name, sw_caches[key].limit );
      }
    }
  }
});

Here, the Service Worker listens for inbound messages and responds to the “clean up” request by running trimCache() on each of the cache buckets with a defined limit.

This approach is by no means elegant, but it works. It would be far better to make decisions about purging cached responses based on how frequently each item is accessed and/or how much room it takes up on disk. (Removing cached items based purely on when they were cached isn’t nearly as useful.) Sadly, we don’t have that level of detail when it comes to inspecting the caches…yet. I’m actually working to address this limitation in the Cache API right now.

Your users always come first

The technologies underlying Progressive Web Apps are continuing to mature, but even if you aren’t interested in turning your site into a PWA, there’s so much you can do today to improve your users’ experiences when it comes to media. And, as with every other form of inclusive design, it starts with centering on your users who are most at risk of having an awful experience.

Draw distinctions between critical, nice-to-have, and superfluous media. Remove the cruft, then optimize the bejeezus out of each remaining asset. Serve your media in multiple formats and sizes, prioritizing the smallest versions first to make the most of high latency and slow connections. If your users say they want to save data, respect that and have a fallback plan in place. Cache wisely and with the utmost respect for your users’ disk space. And, finally, audit your caching strategies regularly—especially when it comes to large media files.Follow these guidelines, and every one of your users—from folks rocking a JioPhone on a rural mobile network in India to people on a high-end gaming laptop wired to a 10 Gbps fiber line in Silicon Valley—will thank you.

It’s an important time to be in voice design. Many of us are turning to voice assistants in these times, whether for comfort, recreation, or staying informed. As the interest in interfaces driven by voice continues to reach new heights around the world, so too will users’ expectations and the best practices that guide their design.

Voice interfaces (also known as voice user interfaces or VUIs) have been reinventing how we approach, evaluate, and interact with user interfaces. The impact of conscious efforts to reduce close contact between people will continue to increase users’ expectations for the availability of a voice component on all devices, whether that entails a microphone icon indicating voice-enabled search or a full-fledged voice assistant waiting patiently in the wings for an invocation.

But voice interfaces present inherent challenges and surprises. In this relatively new realm of design, the intrinsic twists and turns in spoken language can make things difficult for even the most carefully considered voice interfaces. After all, spoken language is littered with fillers (in the linguistic sense of utterances like hmm and um), hesitations and pauses, and other interruptions and speech disfluencies that present puzzling problems for designers and implementers alike.

Once you’ve built a voice interface that introduces information or permits transactions in a rich way for spoken language users, the easy part is done. Nonetheless, voice interfaces also surface unique challenges when it comes to usability testing and robust evaluation of your end result. But there are advantages, too, especially when it comes to accessibility and cross-channel content strategy. The fact that voice-driven content lies on the opposite extreme of the spectrum from the traditional website confers it an additional benefit: it’s an effective way to analyze and stress-test just how channel-agnostic your content truly is.

The quandary of voice usability

Several years ago, I led a talented team at Acquia Labs to design and build a voice interface for Digital Services Georgia called Ask GeorgiaGov, which allowed citizens of the state of Georgia to access content about key civic tasks, like registering to vote, renewing a driver’s license, and filing complaints against businesses. Based on copy drawn directly from the frequently asked questions section of the Georgia.gov website, it was the first Amazon Alexa interface integrated with the Drupal content management system ever built for public consumption. Built by my former colleague Chris Hamper, it also offered a host of impressive features, like allowing users to request the phone number of individual government agencies for each query on a topic.

Designing and building web experiences for the public sector is a uniquely challenging endeavor due to requirements surrounding accessibility and frequent budgetary challenges. Out of necessity, governments need to be exacting and methodical not only in how they engage their citizens and spend money on projects but also how they incorporate new technologies into the mix. For most government entities, voice is a completely different world, with many potential pitfalls.

At the outset of the project, the Digital Services Georgia team, led by Nikhil Deshpande, expressed their most important need: a single content model across all their content irrespective of delivery channel, as they only had resources to maintain a single rendition of each content item. Despite this editorial challenge, Georgia saw Alexa as an exciting opportunity to open new doors to accessible solutions for citizens with disabilities. And finally, because there were relatively few examples of voice usability testing at the time, we knew we would have to learn on the fly and experiment to find the right solution.

Eventually, we discovered that all the traditional approaches to usability testing that we’d executed for other projects were ill-suited to the unique problems of voice usability. And this was only the beginning of our problems.

How voice interfaces improve accessibility outcomes

Any discussion of voice usability must consider some of the most experienced voice interface users: people who use assistive devices. After all, accessibility has long been a bastion of web experiences, but it has only recently become a focus of those implementing voice interfaces. In a world where refreshable Braille displays and screen readers prize the rendering of web-based content into synthesized speech above all, the voice interface seems like an anomaly. But in fact, the exciting potential of Amazon Alexa for disabled citizens represented one of the primary motivations for Georgia’s interest in making their content available through a voice assistant.

Questions surrounding accessibility with voice have surfaced in recent years due to the perceived user experience benefits that voice interfaces can offer over more established assistive devices. Because screen readers make no exceptions when they recite the contents of a page, they can occasionally present superfluous information and force the user to wait longer than they’re willing. In addition, with an effective content schema, it can often be the case that voice interfaces facilitate pointed interactions with content at a more granular level than the page itself.

Though it can be difficult to convince even the most forward-looking clients of accessibility’s value, Georgia has been not only a trailblazer but also a committed proponent of content accessibility beyond the web. The state was among the first jurisdictions to offer a text-to-speech (TTS) phone hotline that read web pages aloud. After all, state governments must serve all citizens equally—no ifs, ands, or buts. And while these are still early days, I can see voice assistants becoming new conduits, and perhaps more efficient channels, by which disabled users can access the content they need.

Managing content destined for discrete channels

Whereas voice can improve accessibility of content, it’s seldom the case that web and voice are the only channels through which we must expose information. For this reason, one piece of advice I often give to content strategists and architects at organizations interested in pursuing voice-driven content is to never think of voice content in isolation. Siloing it is the same misguided approach that has led to mobile applications and other discrete experiences delivering orphaned or outdated content to a user expecting that all content on the website should be up-to-date and accessible through other channels as well.

After all, we’ve trained ourselves for many years to think of content in the web-only context rather than across channels. Our closely held assumptions about links, file downloads, images, and other web-based marginalia and miscellany are all aspects of web content that translate poorly to the conversational context—and particularly the voice context. Increasingly, we all need to concern ourselves with an omnichannel content strategy that straddles all those channels in existence today and others that will doubtlessly surface over the horizon.

With the advantages of structured content in Drupal 7, Georgia.gov already had a content model amenable to interlocution in the form of frequently asked questions (FAQs). While question-and-answer formats are convenient for voice assistants because queries for content tend to come in the form of questions, the returned responses likewise need to be as voice-optimized as possible.

For Georgia.gov, the need to preserve a single rendition of all content across all channels led us to perform a conversational content audit, in which we read aloud all of the FAQ pages, putting ourselves in the shoes of a voice user, and identified key differences between how a user would interpret the written form and how they would parse the spoken form of that same content. After some discussion with the editorial team at Georgia, we opted to limit calls to action (e.g., “Read more”), links lacking clear context in surrounding text, and other situations confusing to voice users who cannot visualize the content they are listening to.

Here’s a table containing examples of how we converted certain text on FAQ pages to counterparts more appropriate for voice. Reading each sentence aloud, one by one, helped us identify cases where users might scratch their heads and say “Huh?” in a voice context.

In areas like content strategy and content governance, content audits have long been key to understanding the full picture of your content, but it doesn’t end there. Successful content audits can run the gamut from automated checks for orphaned content or overly wordy articles to more qualitative analyses of how content adheres to a specific brand voice or certain design standards. For a content strategy truly prepared for channels both here and still to come, a holistic understanding of how users will interact with your content in a variety of situations is a baseline requirement today.

Other conversational interfaces have it easier

Spoken language is inherently hard. Even the most gifted orators can have trouble with it. It’s littered with mistakes, starts and stops, interruptions, hesitations, and a vertiginous range of other uniquely human transgressions. The written word, because it’s committed instantly to a mostly permanent record, is tame, staid, and carefully considered in comparison.

When we talk about conversational interfaces, we need to draw a clear distinction between the range of user experiences that traffic in written language rather than spoken language. As we know from the relative solidity of written language and literature versus the comparative transience of spoken language and oral traditions, in many ways the two couldn’t be more different from one another. The implications for designers are significant because spoken language, from the user’s perspective, lacks a graphical equivalent to which those scratching their head can readily refer. We’re dealing with the spoken word and aural affordances, not pixels, written help text, or visual affordances.

Why written conversational interfaces are easier to evaluate

One of the privileges that chatbots and textbots enjoy over voice interfaces is the fact that by design, they can’t hide the previous steps users have taken. Any conversational interface user working in the written medium has access to their previous history of interactions, which can stretch back days, weeks, or months: the so-called backscroll. A flight passenger communicating with an airline through Facebook Messenger, for example, knows that they can merely scroll up in the chat history to confirm that they’ve already provided the company with their e-ticket number or frequent flyer account information.

This has outsize implications for information architecture and conversational wayfinding. Since chatbot users can consult their own written record, it’s much harder for things to go completely awry when they make a move they didn’t intend. Recollection is much more difficult when you have to remember what you said a few minutes ago off the top of your head rather than scrolling up to the information you provided a few hours or weeks ago. An effective chatbot interface may, for example, enable a user to jump back to a much earlier, specific place in a conversation’s history.An effective chatbot interface may, for example, enable a user to jump back to a much earlier, specific place in a conversation’s history. Voice interfaces that live perpetually in the moment have no such luxury.

Eye tracking only works for visual components

In many cases, those who work with chatbots and messaging bots (especially those leveraging text messages or other messaging services like Facebook Messenger, Slack, or WhatsApp) have the unique privilege of benefiting from a visual component. Some conversational interfaces now insert other elements into the conversational flow between a machine and a person, such as embedded conversational forms (like SPACE10’s Conversational Form) that allow users to enter rich input or select from a range of possible responses.

The success of eye tracking in more traditional usability testing scenarios highlights its appropriateness for visual interfaces such as websites, mobile applications, and others. However, from the standpoint of evaluating voice interfaces that are entirely aural, eye tracking serves only the limited (but still interesting from a research perspective) purpose of assessing where the test subject is looking while speaking with an invisible interlocutor—not whether they are able to use the interface successfully. Indeed, eye tracking is only a viable option for voice interfaces that have some visual component, like the Amazon Echo Show.

Think-aloud and concurrent probing interrupt the conversational flow

A well-worn approach for usability testing is think-aloud, which allows for users working with interfaces to present their frequently qualitative impressions of interfaces verbally while interacting with the user experience in question. Paired with eye tracking, think-aloud adds considerable dimension to a usability test for visual interfaces such as websites and web applications, as well as other visually or physically oriented devices.

Another is concurrent probing (CP). Probing involves the use of questions to gather insights about the interface from users, and Usability.gov describes two types: concurrent, in which the researcher asks questions during interactions, and retrospective, in which questions only come once the interaction is complete.

Conversational interfaces that utilize written language rather than spoken language can still be well-suited to think-aloud and concurrent probing approaches, especially for the components in the interface that require manual input, like conversational forms and other traditional UI elements interspersed throughout the conversation itself.

But for voice interfaces, think-aloud and concurrent probing are highly questionable approaches and can catalyze a variety of unintended consequences, including accidental invocations of trigger words (such as Alexa mishearing “selected” as “Alexa”) and introduction of bad data (such as speech transcription registering both the voice interface and test subject). After all, in a hypothetical think-aloud or CP test of a voice interface, the user would be responsible for conversing with the chatbot while simultaneously offering up their impressions to the evaluator overseeing the test.

Voice usability tests with retrospective probing

Retrospective probing (RP), a lesser-known approach for usability testing, is seldom seen in web usability testing due to its chief weakness: the fact that we have awful memories and rarely remember what occurred mere moments earlier with anything that approaches total accuracy. (This might explain why the backscroll has joined the pantheon of rigid recordkeeping currently occupied by cuneiform, the printing press, and other means of concretizing information.)

For users of voice assistants lacking scrollable chat histories, retrospective probing introduces the potential for subjects to include false recollections in their assessments or to misinterpret the conclusion of their conversations. That said, retrospective probing permits the participant to take some time to form their impressions of an interface rather than dole out incremental tidbits in a stream of consciousness, as would more likely occur in concurrent probing.

What makes voice usability tests unique

Voice usability tests have several unique characteristics that distinguish them from web usability tests or other conversational usability tests, but some of the same principles unify both visual interfaces and their aural counterparts. As always, “test early, test often” is a mantra that applies here, as the earlier you can begin testing, the more robust your results will be. Having an individual to administer a test and another to transcribe results or watch for signs of trouble is also an effective best practice in settings beyond just voice usability.

Interference from poor soundproofing or external disruptions can derail a voice usability test even before it begins. Many large organizations will have soundproof rooms or recording studios available for voice usability researchers. For the vast majority of others, a mostly silent room will suffice, though absolute silence is optimal. In addition, many subjects, even those well-versed in web usability tests, may be unaccustomed to voice usability tests in which long periods of silence are the norm to establish a baseline for data.

How we used retrospective probing to test Ask GeorgiaGov

For Ask GeorgiaGov, we used the retrospective probing approach almost exclusively to gather a range of insights about how our users were interacting with voice-driven content. We endeavored to evaluate interactions with the interface early and diachronically. In the process, we asked each of our subjects to complete two distinct tasks that would require them to traverse the entirety of the interface by asking questions (conducting a search), drilling down into further questions, and requesting the phone number for a related agency. Though this would be a significant ask of any user working with a visual interface, the unidirectional focus of voice interface flows, by contrast, reduced the likelihood of lengthy accidental detours.

Here are a couple of example scenarios:

We also peppered users with questions after the test concluded to learn about their impressions through retrospective probing:

• “On a scale of 1–5, based on the scenario, was the information you received helpful? Why or why not?”
• “On a scale of 1–5, based on the scenario, was the content presented clear and easy to follow? Why or why not?”
• “What’s the answer to the question that you were tasked with asking?”

Because state governments also routinely deal with citizen questions having to do with potentially traumatic issues such as divorce and sexual harassment, we also offered the choice for participants to opt out of certain categories of tasks.

While this testing procedure yielded compelling results that indicated our voice interface was performing at the level it needed to despite its experimental nature, we also ran into considerable challenges during the usability testing process. Restoring Amazon Alexa to its initial state and troubleshooting issues on the fly proved difficult during the initial stages of the implementation, when bugs were still common.

In the end, we found that many of the same lessons that apply to more storied examples of usability testing were also relevant to Ask GeorgiaGov: the importance of testing early and testing often, the need for faithful yet efficient transcription, and the surprising staying power of bugs when integrating disparate technologies. Despite Ask GeorgiaGov’s many similarities to other interface implementations in terms of technical debt and the role of usability testing, we were overjoyed to hear from real Georgians whose engagement with their state government could not be more different from before.

Conclusion

Many of us may be building interfaces for voice content to experiment with newfangled channels, or to build for disabled people and people newer to the web. Now, they are necessities for many others, especially as social distancing practices continue to take hold worldwide. Nonetheless, it’s crucial to keep in mind that voice should be only one component of a channel-agnostic strategy equipped for content ripped away from its usual contexts. Building usable voice-driven content experiences can teach us a great deal about how we should envisage our milieu of content and its future in the first place.

Gone are the days when we could write a page in HTML and call it a day; content now needs to be rendered through synthesized speech, augmented reality overlays, digital signage, and other environments where users will never even touch a personal computer. By focusing on structured content first and foremost with an eye toward moving past our web-based biases in developing our content for voice and others, we can better ensure the effectiveness of our content on any device and in any form factor.

Eight months after we finished building Ask GeorgiaGov in 2017, we conducted a retrospective to inspect the logs amassed over the past year. The results were striking. Vehicle registration, driver’s licenses, and the state sales tax comprised the most commonly searched topics. 79.2% of all interactions were successful, an achievement for one of the first content-driven Alexa skills in production, and 71.2% of all interactions led to the issuance of a phone number that users could call for further information.

But deep in the logs we implemented for the Georgia team’s convenience, we found a number of perplexing 404 Not Found errors related to a search term that kept being recorded over and over again as “Lawson’s.” After some digging and consulting the native Georgians in the room, we discovered that one of our dear users with a particularly strong drawl was repeatedly pronouncing “license” in her native dialect to no avail.

As this anecdote highlights, just as no user experience can be truly perfect for everyone, voice content is an environment where imperfections can highlight considerations we missed in developing cross-channel content. And just as we have much to learn when it comes to the new shapes content can take as it jumps off the screen and out the window, it seems our voice interfaces still have a ways to go before they take over the world too.

Special thanks to Nikhil Deshpande for his feedback during the writing process.

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