The good news is there is no shortage of awesome WordPress themes that can help you create an engaging and well-functioning website. The not-so-good news is that the options open to you can be overwhelming because of the thousands of great WordPress themes available. Finding one you can rely on to help you quickly create […]

The post 10 Awesome WordPress Themes to Check Out in 2024 appeared first on WebAppers.

The importance of mobile design really cannot be exaggerated these days. In 2014, 60 percent of web traffic came from a mobile device. That’s well over half, and more than enough reason to convince any sane person of the importance of mobile first design.But building a top smartphone app is tough. Contrary to what most […]

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The post Illustrator Tutorial: Design a Retro VHS Cover Inspired Poster appeared first on Spoon Graphics.

Follow along with this photo compositing Photoshop tutorial to create a surreal space scene with a vibrant neon light effect. We’ll use assets from a free sample pack of the Ultimate Universe Creator product that’s exclusively available for Spoon Graphics viewers to download. I’ll show you how to compose the various space-themed graphics to make […]

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In addition to our Leveler, Denoiser, and Adaptive 'Hi-Pass' Filter, we now release the missing equalization feature with the new Auphonic AutoEQ.
The AutoEQ automatically analyzes and optimizes the frequency spectrum of a voice recording, to remove sibilance (De-esser) and to create a clear, warm, and pleasant sound - listen to the audio examples below to get an idea about what it does.

Screenshot of manually adjusted example settings for the equalizer plug-in 'Pro-Q3' by fabfilter.

What is Equalization and why is it difficult?

Equalization (EQ) in audio recording and reproduction is the process of adjusting the volume of different frequency bands within a signal.
The following vocal EQ cheat sheet, published by Producer Hive, will give you a small impression, of what can be influenced by equalizing:

Vocal EQ Cheat Sheet by Producer Hive.

On the other hand, it is very easy to ruin a good voice recording with manual heavy-handed equalization, resulting in voices, that sound very sharp or muddy or even like the speaker had a blocked nose.
Besides the skill and experience of an audio engineer, manual adjustments of frequencies also require a very good and linear studio playback device. For example, performing manual equalization with strongly bass-heavy speakers would most likely lead to a very sharp, unpleasant listening experience using treble-heavy headphones.

For singletrack productions with more than one speaker, equalizing is also a very complex and time-consuming process, as every voice has its unique frequency spectrum and needs its own equalization. One could separate speakers with cuts or create a track envelope to fade from one speaker to another, however, any solution is a very tedious job, if you do it by hand.

That is where the Auphonic AutoEQ comes in! All those steps are now available in just one click!

How does the Auphonic AutoEQ work?

The Auphonic Web Service analyzes your audio content and classifies the audio file into small and meaningful segments like music, silence, different speakers, etc. to process every single segment with the best matching algorithms.
All our features like the Adaptive Leveler, Dynamic Denoising, Adaptive 'Hi-Pass' Filtering, and now the new AutoEQ filter option are built on top of this basic processing.

Using Auphonic AutoEQ, spectral EQ profiles are created for each speaker separately and permanently changing over time. The aim of those time-dependent EQ profiles is to create a constant, pleasant sound in the output file even if there are slightly changing voices in the record, for example, due to modified speaker-microphone positions.

Audio Examples

Here are two short audio examples, which demonstrate some features of our AutoEQ.
We recommend listening with headphones so you can hear all the details.

Example 1. Female Speaker with Background Music

In the following example (BCB: The Voices of Bainbridge Island) of a female narrator speaking while background music is playing, you can easily recognize quite sharp 'sss' sounds in the female voice. This sharpness in the female voice is removed by the so-called De-essing feature of the Auphonic AutoEQ, while the background music is not changed.

Example 2. Dialog of Male and Female Speakers

The next example (BCB: The Voices of Bainbridge Island) shows how the AutoEQ optimizes a singletrack record containing two speakers with different voice characteristics. Our AutoEQ algorithms analyze each voice separately and calculate the matching frequency adjustments to optimize the voice of every single speaker.

AutoEQ Beta Integration in the Auphonic Web Service

To use the Auphonic AutoEQ, you just have to create a production or preset as you are used to, toggle “Advanced Parameters” on the top right in the section “Audio Algorithms” and select “Voice AutoEQ” within “Filtering”:

For a first test period, the AutoEQ will only be available for Beta and paying users, to incorporate your feedback and finalize an optimized version.
If you are a free user but want to try Auphonic AutoEQ: please just ask for access!

Practical Tips

For best results using Auphonic AutoEQ, however, it is still necessary, that your audio content is of sufficiently good quality, as no equalizer can make up frequencies that are not there in the first place. Audio files with low bitrates often lack important frequencies, that cannot be recovered by equalizing. AutoEQ is just a feature to boost or cut individual frequency bands, not a bandwidth extension. For more information about required audio quality, see the former blog post: Audio File Formats and Bitrates for Podcasts.

Another important topic is the definition of the 'best result'. Equalizing is a very subjective task, that differs a lot depending on every personal opinion. So Auphonic AutoEQ is set up to follow quite conservative rules of equalizing and rather apply subtle tweaks and remove obvious problems, than support personal preferences. This also means, your record will experience no significant changes from Auphonic AutoEQ if it sounds reasonably OK or pretty good already.

Conclusion

Auphonic audio post production algorithms keep getting better and better in leaps and bounds lately, offering you new Beta Features: Beta Auphonic Denoiser, Beta Auphonic Speech Recognition, and Beta Auphonic AutoEQ.
Right now we are fine-tuning all our current Beta Features with high intensity to release a new upgraded version of our Auphonic Web Service as soon as possible.
Please watch this channel for further updates – soon to come.

If you have any feedback for us or want to become a Beta user, you are very welcome to comment directly in our production interface or to contact us via email!

Cutting audio can be a rather tedious task. It requires a decent amount of time and is quite repetitive. Often silence segments, like speech breaks or breathing pauses, make cutting audio necessary in the first place.

Photo by Daniel Schludi on Unsplash

We introduce our new automatic silence cutting feature! It will make your life easier by saving you the time you would normally require to cut silence segments in your recordings.

Why do you need to cut silence segments?

Silence segments occur in your audio recordings naturally. They can be due to short speech breaks or breathing pauses. It's also possible, that at the beginning of a recording equipment needs to be re-adjusted, which also may result in a few seconds of silence.

Usually, listeners do not want to hear silence segments. The reason is easy: silence is redundant filler content. Hence, silence segments need to be cut to achieve a high-quality listening experience. Locating the segments and cutting them manually is tedious though and takes a decent amount of time for longer recordings.

This is why we developed and released our own automatic silence cutting feature.

How do we cut silence for you?

Our automatic silence cutting algorithm detects and cuts silence segments reliably. All you need to do is to enable the algorithm in your production - no further settings are required! This is the easiest possible way for you to cut silence in an audio file.

How to enable silence cutting for your production.

In our audio processing system, silence cutting is a multi-stage algorithm. We use our sophisticated voice activity detection algorithms to detect what is useful content and what is silence. Then we cut the silence parts and crossfade the remaining audio segments to make sure no audio artifacts are introduced. When cutting we ensure that intended speech breaks, e.g. between two sentences, remain untouched.

When we cut any audio, we make sure that chapter marks and speech recognition transcripts are adapted accordingly. Additionally, when exporting to other external services we make sure the cut tracks are exported and correctly labeled.

Audio Examples

Let's listen to two audio examples.

Example 1 (Singletrack production)

Here we have a singletrack production with three silence segments. The segments are located at the beginning of recording, between the first and the second "Hi" as well as at the end. Each silence segment is cut down to a length which still sounds natural, but does not annoy the listener.

The breathing onsets, which happen straight before voice kicks in again, are not cut. This makes sure that the character of the recording remains natural.

For this example, we also activated our new AutoEQ feature to remove pops in the audio.

Here is also a screenshot of how the result looks in our audio player. The gray areas show where our audio processing system cut the silence.

The result of example 01, as displayed by our Audio Inspector.

Thx to the Feel Free to Deviate podcast for providing this recording.

Example 2 (Multitrack production)

Let's also look at silence cutting in a multitrack production. This small excerpt of the TVEye podcast contains a music track and three speaker tracks. Before the intro music kicks in, there are a few seconds of silence.

The few seconds of silence at the beginning of the file are cut. After that, no further cuts are applied though to make sure the background music remains intact.

This is how the result of example 02 looks in our Audio Inspector.

Silence Cutting in our Audio Inspector

As you may have seen already in the examples, the cut segments are displayed as checked grey areas in the Audio Inspector. This is how they will be displayed by default.

Cut segments are displayed as checked gray areas by default.

During playback, the Audio Inspector will automatically skip these cut segments on the master track and play the silence segments if you activate the input track. This way, you can check each segment that was cut.

It's also possible to hide the cut segments. The following picture shows you how to do that.

You can also hide cut segments.

First, you must click onto the "?" icon in the bottom right corner to show the Audio Inspector options. Then you must toggle the "Silence Cut Region" switch. After that, the cut regions are not displayed anymore, and also won't be played back on the input track anymore.

If you click onto "Show Stats", you can activate the audio processing statistics. These statistics show you how much of your audio was cut, as well as the resulting track length after the cuts were applied.

The processing statistics tell you more about how much audio was cut.

Conclusion

With our automatic silence cutting feature, we went one step further towards the perfect audio assistant. Audio editing has been a tedious-but-necessary task for a long time, but with our automatic silence cutting feature, we just made it easier for you!

Feel free to send us your feedback - how do you like our new feature? Also, make sure to follow us, as we will release more automatic cutting algorithms for you in the future!

We're thrilled to introduce our Automatic Shownotes and Chapters feature. This AI-powered tool effortlessly generates concise summaries, intuitive chapter timestamps and relevant keywords for your podcasts, audio and video files.
See our Examples and the How To section below for details.

Why do I need Shownotes and Chapters?

In addition to links and other information, shownotes contain short summaries of the main topics of your episode, and inserted chapter marks allow you to timestamp sections with different topics of a podcast or video. This makes your content more accessible and user-friendly, enabeling listeners to quickly navigate to specific sections of the episode or find a previous episode to brush up on a particular topic.

Shownotes are also very likely to boost your show's Search Engine Optimization and eventually its popularity, leading to an increase in listeners.

However, especially structuring the content and finding useful positions for chapter marks is a very time-consuming process, that can be fully automated with our new feature.

Besides the obvious use of creating shownotes and chapters for podcasts, you can also use our new feature to easily generate an abstract of your lecture recording, take the summary of your show as the starting point for a social media post, or choose your favourite chapter title as the podcast name.

What happens behind the Scenes?

When the Automatic Shownotes and Chapters feature is selected, the first step is speech transcription by either our internal Auphonic Whisper ASR or any integrated External ASR Service of your choice.

Some open source tools and ChatGPT will then summarize the ASR resulting text in different levels of detail, analyze the content to identify sections with the different topics discussed, and finally complete each section with timestamps for easy navigation.
Beginning with the generation of a Long Summary, the number of characters is further reduced for a Brief Summary and from the brief summary a Subtitle and some Keywords for the main topics are extracted.

Depending on the duration of the input audio or video file, the level of detail of the thematic sections is also slightly adjusted, resulting in a reasonable number of chapters for very short 5-minute audio files as well as for long 180-minute audio files.

How to automatically generate Shownotes and Chapters in Auphonic

If you are a paying or beta user, you can automatically generate shownotes and chapters by checking the Automatic Shownotes and Chapters Checkbox in the Auphonic singletrack or multitrack Production Form with any of our ASR Services enabled.
Once your production is done, the generated data will show up in your transcript result files and in the well-known Auphonic Transcript Editor above the speech recognition transcript section.
By clicking on a chapter title in the Chapters section of the transcript editor, you can jump directly to that chapter in your transcript to review and edit that section.

Unless you have manually entered content before, the generated data will also be automatically stored in your audio files' metadata as follows:

• Generated Long Summary stored in metadata field Summary.
• Generated Subtitle stored in metadata field Subtitle.
• Generated Keywords stored in metadata field Tags.
• Generated Timestamps for thematic sections stored as Start Time of Chapters Marks.
• Generated Headlines for thematic sections stored as Chapter Title of Chapters Marks.

Please note that not all of our supported Output File Formats are designed to use metadata.
For details see our previous blog posts: ID3 Tags Metadata (used in MP3 output files), Vorbis Comment Metadata (used in FLAC, Opus and Ogg Vorbis output files) and MPEG-4 iTunes-style Metadata (used in AAC, M4A/M4B/MP4 and ALAC output files).

Example

As a real-life example, we automatically generated shownotes and chapters for the Lex Fridman Podcast #367: "Sam Altman: OpenAI CEO on GPT-4, ChatGPT, and the Future of AI".

Check out our transcript and generated shownotes:
LexFridmanPodcast367-transcript.html

Conclusion

The automatic generation of shownotes and chapters is a huge time-saver for podcasters and video creators, as it speeds up the tedious process of manually structuring and summarizing your content.

For now it is available for all paying or beta users. If you would like to become a beta user, or have any questions or feedback, please do not hesitate to contact us!

We all know the problem: the content is perfectly prepared, and everything is in place, but the moment you hit the record button, your brain freezes, and what pops out of your mouth is a rain of “ums”, “uhs”, and “mhs” that no listener would enjoy.
Cleaning up a record like that by manually cutting out every single filler word is a painstaking task.

So we heard your requests to automate the filler word removing task, started implementing it, and are now very happy to release our new Automatic Filler Cutter feature. See our Audio Examples and Usage Instructions below.

What is removed?

While the definition of filler words is not the same, depending on who you ask, some words can be used as filler as well as content. For example, “like”, “well”, “you know”, etc. cannot be removed without the risk of removing also content and destroying sentences, even if those words are used as filler words in some cases.

Therefore, we decided to focus on the removal of the obvious fillers, namely any kind of “ums”, “uhs”, “mhs”, German “ähm”, “äh”, “öh”, French “euh”, “euhm” and similar.

Audio Examples

1. English Male Speaker

The first audio example is an excerpt from the interview “From Racing Failure to Red Bull Champion: The Untold Christian Horner Story”. Our algorithm found and removed a remarkable ten filler words in this 45-second snippet:

Screenshot of the Auphonic Audio Inspector: each pale red shaded area corresponds to a cut-out filler word.

2. Austrian-German Female Speaker

The following example is an interview with the Austrian Ex-Foreign Minister, Karin Kneissl, who uses seven filler words within 26 seconds:

Usage Instructions

To use the Auphonic Automatic Filler Cutter feature, you just have to create a production or preset as you are used to and select “Cut Fillers” for “Automatic Cutting” in the section “Audio Algorithms”:

When your production is done, all cut-out filler words will appear as pale red shaded areas in the Auphonic Audio Inspector on the production status page, as you can see in the upper screenshot of the Audio Inspector.

If you want to remove silent segments from your audio as well, please also enable our Automatic Silence Cutting feature.

NOTE: Our Automatic Cutting features (for filler and silence) are not available for video files!

Behind the Scenes

For the training of our Automatic Filler Cutter AI-Algorithm, we created datasets that contain manually labeled audio files, collected from 'real world' audio data. So far, we have labeled, trained, and tested the system with English, German, Spanish, and French data.

However, in the Auphonic Web Service, you can activate and test the Automatic Filler Word Cutter for all languages. We would be very happy to hear how the filler removal works out for completely different-sounding languages from, e.g., the Asian, African, or Slavic language families.

Please send us feedback on any problems or error patterns you discover! This will help us generate specific data for the training to improve the algorithm and eliminate your problems.

Conclusion

Automatic filler word cutting is a powerful tool for podcasters looking to enhance the quality of their content. It boosts clarity and professionalism, all while making your editing process more efficient. Some users, however, see a touch of authenticity in filler words within podcasts. So, we leave it up to you to enable or disable the Automatic Filler Cutter feature for your next Auphonic production, depending on your desired style.

We are currently working on filler word cutting optimizations for more languages, so watch our channels to get all the news on our upgrades!

If you have any feedback for us – how the filler cutter is working in your language, what you do or don't like, what you miss, what else you would want to remove from your audio besides silence and filler words, etc. – you are welcome to contact us via email or directly comment on our production interface!

For those of you who like to be in control of every applied cut, we are introducing an update for our Automatic Silence and Filler Word Cutting Algorithms today: The export of Cut Lists allows you to import cuts into your favorite audio/video editor to check and apply the cuts to your files manually.
Thanks to your great feedback, we were able to update our “Filler Word Cutting” algorithm as well.

Cut Lists Export

We now provide the export of various formats of “Cut Lists” in the Auphonic Web Service.
You can use these formats to modify and apply cuts in your post production audio or video editing program:

Screenshot of the Reaper DAW with imported “ReaperRegions.csv”: pale red regions display filler words and pale gray regions mark silence.

To generate the cut lists, choose “Cut List (Filler and Silence)” in the “Output Files” section. By selecting the correct “Ending” you can export the cut lists to a format that is suitable for your post production audio or video editor:

We support regions and EDL (edit decision list) formats:

• Region formats (“AudacityRegions.txt”, “AuditionRegions.csv” and “ReaperRegions.csv”) list filler and silence cut regions with their respective start and end timestamps.
  You can import those cut region lists into your existing Audacity, Audition, or Reaper projects. There you can edit the cut positions to your liking by deleting, moving, or adding individual cut positions. After that, you may apply the cuts manually.
• EDL (edit decision list) formats, “SamplitudeReaper.edl”, “FinalCutProLegacy.xml”, “FinalCutProX.xml” and “DaVinciResolve.edl” (also known as “cmx3600” format and compatible with various editors), can be imported in your software to automatically apply cuts from the EDL file. Depending on the software you use, you may also edit individual cuts manually before applying them. Be aware though that in some editors it may not be possible to add them to an existing project. If this is the case, simply open a new project with the EDL file instead.

Please just let us know if we do not yet provide a cut list format for your favorite audio or video editing program!

Export Uncut Audio

To only detect fillers/silence but NOT cut them, choose the “Export Uncut Audio” mode for “Automatic Cutting” in “Audio Algorithms”. Then you can query cutting times via our API or select your favorite Cut List format as “Output File” to only export cut times for later editing, but without applying cuts during the Auphonic audio post production.

Using the option “Export Uncut Audio”, it is also possible to use our cutting algorithms for video productions. In this case, we will just detect and report cuts, and you can import and apply them in your favorite video editing program afterwards.

Filler Word Cutting Updates

Thanks to your great feedback, we've been able to further optimize our Automatic Filler Word Cutting algorithm.
By now you probably know that our filler word cutter removes all types of “uhm”, “uh”, “mh”, “ähm”, “euh”, “eh” and similar sounds. If you haven't heard about it yet, our release blog post might be a good starting point.

• Enhanced Fade Curves
  We noticed that due to reverb or background noise in input files, some filler cuts did not sound as smooth as they should have. To prevent such rough cuts, we trained our filler detection models with more diverse speech data and compared different fade curve approaches. Now the filler detection is much more robust against noise. Additionally, we developed an asymmetrical fade solution, which, in our opinion, makes the cuts almost inaudible.

  We nonetheless recommend, though, that you use filler cutting in combination with our Dynamic Denoising or Speech Isolation algorithms. These algorithms remove heavy reverb or noise and thus prevent noise artifacts during cutting.

• Handling of Affirmative Sounds
  Some of you were bothered by the fact that affirmative sounds, like “mhm”, “aha”, and “yeah” were cut along with filler words. Driven by your feedback, we tweaked our filler detection algorithm in a way that will remove considerably fewer of these sounds.

• Multitrack Filler Silencing
  We also received requests to optimize filler cutting for crosstalk in Multitrack productions.
  Let's assume that two speech tracks are simultaneously active and one of the two tracks contains a filler word. In this case, we can not cut the filler word in one track without destroying parts of the speech in the other track.
  Our original solution was to skip such a filler. Now, however, we replace it with silence instead. This removes the filler words while preserving all the speech content.

Feedback

If you want to provide us feedback on how you like the updated filler cutting algorithm or about any other features that are missing, you are very welcome to contact us. You can also leave a comment in the feedback section on the status page of your concrete production.

No matter how good your technical equipment might be, it is almost impossible to avoid capturing unwanted in-/exhaling sounds and mouth noises during voice recordings. After some users asked for an automatic removal of such sounds to improve the audio quality, we got to work and are now proud to present a major upgrade to our Denoiser, including the automatic removal of mouth noises and a new “Remove Breathings” option!
Check out our Audio Examples and the Getting Started Guide below.

What is new?

• Remove Breathings: When the new “Remove Breathings” option is enabled, all the inhalation and exhalation sounds will be muted like all the other noises.
• Eliminate Mouth Noises and Eating Sounds: With our upgrade to the Denoiser, we have integrated the elimination of all types of mouth noises, such as smacking, chewing and clicking. These sounds are set to silence in your output file.

NOTE:
By default, mouth noises and breathing segments are muted but not cut. If you want to cut out all silent segments, just add the “Cut Silence” option for “Automatic Cutting” in the audio algorithms.

Audio Examples

1. Example: Breathing Removal

In our first audio example (Freak Show 136), a speaker breathes directly into the microphone, creating a Darth Vader-like effect. This heavy breathing is removed using the “Remove Breathings” algorithm and the Dynamic Denoiser:

2. Example: Mouth Noise and Eating Sounds Elimination

The following example is an excerpt from the Joe Rogan Experience #2054 where Elon Musk and Joe Rogan are eating pizza and talking about how terrible it is for the sound. Listen to how the chewing and smacking sounds are removed after processing with the new Dynamic Denoiser:

Getting Started Guide

For the Auphonic Web Service:

To remove breathing sounds in the Auphonic Web Service, simply create a production or preset as usual and check the “Remove Breathings” checkbox for “Noise Reduction” in the “Audio Algorithms” section.
“Remove Breathings” is only available for Speech Isolation and the Dynamic Denoiser, but NOT for the Static Denoiser.

For the removal of mouth noises, no special settings are required. Just enable the Speech Isolation or the Dynamic Denoise method for Noise Reduction.

For API Use:

To use “Remove Breathings” with the API, set the "denoisemethod" to dynamic or speech_isolation and the "debreath" flag to true, as in these two examples:

"algorithms": {
    "denoisemethod": dynamic, "denoiseamount": 100, "debreathamount": 100,
}

"algorithms": {
    "denoisemethod": speech_isolation, "denoiseamount": 12, "debreathamount": 100,
}

For more information about the API, please visit our API help page, where you will also find all other API Audio Algorithm Settings.

Conclusion

Breath and mouth noise removal is essential for podcasters, as it enhances audio clarity and ensures a more professional, polished presentation. By removing distracting sounds, you can maintain listener engagement and provide a seamless listening experience.

Anyway, we hope you enjoy the new features!
If you have any feedback for us on how the breath and mouth noise elimination is working for you, please feel free to contact us via email or directly comment in our production interface!

A new foray into the world of video: Auphonic is proud to announce support for intro and outro videos! With our most recent update you can now seamlessly integrate video intros and outros into your productions, providing a richer and more engaging experience for your audience.

Photo by Jakob Owens on Unsplash

What's new?

For a long time Auphonic has supported video files as the main files of productions. Until recently, intros and outros were limited to audio-only though.

Our new feature now allows you to add video intros and outros to your productions. This means your content can now begin and end with video clips, adding a professional touch and increasing viewer engagement. Whether you're working on podcasts, audiobooks, or any other type of multimedia content: providing your content both in audio form and in video form is now way easier!

Mixing Audio and Video

A key aspect of this feature is the ability to mix audio and video files effortlessly. If your main production file is a video but your intro is an audio file, Auphonic will automatically generate a video for the intro using a standing image from the main video. This ensures a seamless and visually coherent transition between different media types, maintaining the overall quality and flow of your production.

It works the same way for outros as well. When your main production file is a video file but your outro is audio-only we will generate an outro video from a standing image of the main video.

Overlap

We also support overlap for video intros and outros. This means you can have your intros and outros start or end slightly before the main content, creating a smoother transition. However, you should know that overlapping intro and outro videos requires us to place a cut in your video intro and outro. Only this way the the audio will stay in sync with the video.

How to add Intro and Outro Videos

Using our new feature is incredibly simple. You can add video intros and outros the same way you would add audio intros and outros in the production form.

A screenshot of the production form where a video intro and a video outro where selected.

Use Cases

There are many different use cases for our new feature! If you, as an example, regularly release episodes of your podcast both as audio and as video, you can now automatically add a recurring video intro and outro without needing to manually edit your videos.

Or, if you're an audio engineer, you may have a large number of recordings of, let's say, a conference. Instead of having to edit each individual conference recording by hand you now can add a common intro and outro to each conference recording automatically using a batch production.

Supported Video Formats

The world of video is a limitless one, with a sheer endless amount of video codecs, resolutions or frame rates to offer. Naturally, this means we are not able to support every arbitrary video format there is. However, we made sure to support the most commonly used video containers and codecs to make sure that at least 99.5% of all video productions will be possible.

Currently we support the 3 most common video containers: MP4, MKV and MOV. For these containers the following codecs are supported:

• h264: MP4, MKV, MOV
• mpeg4: MP4, MKV, MOV
• mpeg2video: MP4, MKV, MOV
• prores: Only MKV and MOV
• msmpeg4v3: Only MKV and MOV

Any video intro or outro which uses these containers and codecs can be processed by us. Additionally, we make sure that your output video uses a common format. Therefore, if your video intro or outro uses a different codec or container than your main video we will encode the video intro or outro to the setting of the main video.

Given that video demands significantly more computational ressources than audio the video intros and outros may be 1 minute long at max in order to be processed.

Conclusion

The new intro and outro videos feature on Auphonic is designed to give you more creative control and to help you produce professional, engaging content effortlessly. By supporting a variety of codecs and allowing for the mixing of audio and video we aim to support every possible workflow. We invite you to explore this new feature and see how it can enhance your multimedia productions!

Feedback

Would you like us to support another video format? Did you stumble across an issue with your video file(s)? Let us know! Simply drop us a message in our contact form or leave a comment in the feedback section on the status page of your specific production.
We're looking forward to hearing from you!

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The post AI Is About to Change Education Forever (Again) first appeared on Chase Jarvis.

The post AI Is About to Change Education Forever (Again) appeared first on Chase Jarvis.

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The post Playing It Safe? How to Step Outside Your Comfort Zone first appeared on Chase Jarvis.

The post Playing It Safe? How to Step Outside Your Comfort Zone appeared first on Chase Jarvis.

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The post The Spiritual Journey of Entrepreneurs (that Nobody Talks About) first appeared on Chase Jarvis.

The post The Spiritual Journey of Entrepreneurs (that Nobody Talks About) appeared first on Chase Jarvis.

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The post AJ Jacobs: Can You Live Fully by the Constitution in 2024? first appeared on Chase Jarvis.

The post AJ Jacobs: Can You Live Fully by the Constitution in 2024? appeared first on Chase Jarvis.

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The post Signs You’re Putting Yourself Last (+ How to Fix It) first appeared on Chase Jarvis.

The post Signs You’re Putting Yourself Last (+ How to Fix It) appeared first on Chase Jarvis.

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The post You’re Wasting Your Life (Without Even Realizing It) first appeared on Chase Jarvis.

The post You’re Wasting Your Life (Without Even Realizing It) appeared first on Chase Jarvis.

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The post Creative Burnout Destroying Your Passion? (Try These 4 Quick Strategies) first appeared on Chase Jarvis.

The post Creative Burnout Destroying Your Passion? (Try These 4 Quick Strategies) appeared first on Chase Jarvis.

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The post What Are the Common Misconceptions about Digital Trading Services? first appeared on CSS Reset.

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The post Leveraging Automated Market Analyzers: A Developer’s Guide to Building Financial Tools with Web Technologies first appeared on CSS Reset.

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The post How to Create a Computer Settings Icon appeared first on Vectips.

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