As part of a project I am working on, there is a requirement to concatenate multiple pieces of audio data into one large audio file. The audio files are generated from four sources, and the individual files are stored in a Google Cloud storage bucket. Each file is an mp3 file, and it is easy to verify that each individual file is generating correctly (individually, I can play them, edit them in my favourite software, etc.).
To merge the audio files together, a nodejs server loads the files from the Google Cloud storage as an array buffer using an axios POST request. From there, it puts each array buffer into a node Buffer using Buffer.from(), so now we have an array of Buffer objects. Then it uses Buffer.concat() to concatenate the Buffer objects into one big Buffer, which we then convert to Base64 data and send to the client server.
This is cool, but the issue arises when concatenating audio generated from different sources. The 4 sources I mentioned above are Text to Speech software platforms, such as Google Cloud Voice and Amazon Polly. Specifically, we have files from Google Cloud Voice, Amazon Polly, IBM Watson, and Microsoft Azure Text to Speech. Essentially just five text to speech solutions. Again, all individual files work, but when concatenating them together via this method there are some interesting effects.
When the sound files are concatenated, seemingly depending on which platform they originate from, the sound data either will or will not be included in the final sound file. Below is a 'compatibility' table based on my testing:
|------------|--------|--------|-----------|-----|
| Platform / | Google | Amazon | Microsoft | IBM |
|------------|--------|--------|-----------|-----|
| Google | Yes | No | No | No |
|------------|--------|--------|-----------|-----|
| Amazon | | No | No | Yes |
|------------|--------|--------|-----------|-----|
| Microsoft | | | Yes | No |
|------------|--------|--------|-----------|-----|
| IBM | | | | Yes |
|------------|--------|--------|-----------|-----|
The effect is as follows: When I play the large output file, it will always start playing the first sound file included. From there, if the next sound file is compatible, it is heard, otherwise it is skipped entirely (no empty sound or anything). If it was skipped, the 'length' of that file (for example 10s long audio file) is included at the end of the generated output sound file. However, the moment that my audio player hits the point where the last 'compatible' audio has played, it immediately skips to the end.
As a scenario:
Input:
sound1.mp3 (3s) -> Google
sound2.mp3 (5s) -> Amazon
sound3.mp3 (7s)-> Google
sound4.mp3 (11s) -> IBM
Output:
output.mp3 (26s) -> first 10s is sound1 and sound3, last 16s is skipped.
In this case, the output sound file would be 26s seconds long. For the first 10 seconds, you would hear the sound1.mp3 and sound3.mp3 played back to back. Then at 10s (at least playing this mp3 file in firefox) the player immediately skips to the end at 26s.
My question is: Does anyone have any ideas why sometimes I can concatenate audio data in this way, and other times I cannot? And how come there is this 'missing' data included at the end of the output file? Shouldn't concatenating the binary data work in all cases if it works for some cases, as all the files have mp3 encoding? If I am wrong please let me know what I can do to successfully concatenate any mp3 files :)
I can provide my nodeJS backend code, but the process and methods used are described above.
Thanks for reading?
Potential Sources of Problems
Sample Rate
44.1 kHz is often used for music, as it's what is used on CD audio. 48 kHz is usually used for video, as it's what was used on DVDs. Both of those sample rates are much higher than is required for speech, so it's likely that your various text-to-speech providers are outputting something different. 22.05 kHz (half of 44.1 kHz) is common, and 11.025 kHz is out there too.
While each frame specifies its own sample rate, making it possible to generate a stream with varying sample rates, I've never seen a decoder attempt to switch sample rates mid-stream. I suspect that the decoder is skipping these frames, or maybe even skipping over an arbitrary block until it gets consistent data again.
Use something like FFmpeg (or FFprobe) to figure out what the sample rates of your files are:
ffmpeg -i sound2.mp3
You'll get an output like this:
Duration: 00:13:50.22, start: 0.011995, bitrate: 192 kb/s
Stream #0:0: Audio: mp3, 44100 Hz, stereo, fltp, 192 kb/s
In this example, 44.1 kHz is the sample rate.
Channel Count
I'd expect your voice MP3s to be in mono, but it wouldn't hurt to check to be sure. As with above, check the output of FFmpeg. In my example above, it says stereo.
As with sample rate, technically each frame could specify its own channel count but I don't know of any player that will pull off switching channel count mid-stream. Therefore, if you're concatenating, you need to make sure all the channel counts are the same.
ID3 Tags
It's common for there to be ID3 metadata at the beginning (ID3v2) and/or end (ID3v1) of the file. It's less expected to have this data mid-stream. You would want to make sure this metadata is all stripped out before concatenating.
MP3 Bit Reservoir
MP3 frames don't necessarily stand alone. If you have a constant bitrate stream, the encoder may still use less data to encode one frame, and more data to encode another. When this happens, some frames contain data for other frames. That way, frames that could benefit from the extra bandwidth can get it while still fitting the whole stream within a constant bitrate. This is the "bit reservoir".
If you cut a stream and splice in another stream, you may split up a frame and its dependent frames. This typically causes an audio glitch, but may also cause the decoder to skip ahead. Some badly behaving decoders will just stop playing altogether. In your example, you're not cutting anything so this probably isn't the source of your trouble... but I mention it here because it's definitely relevant to the way you're working these streams.
See also: http://wiki.hydrogenaud.io/index.php?title=Bit_reservoir
Solutions
Pick a "normal" format, resample and rencode non-conforming files
If most of your sources are all the exact same format and only one or two outstanding, you could convert the non-conforming file. From there, strip ID3 tags from everything and concatenate away.
To do the conversion, I'd recommend kicking it over to FFmpeg as a child process.
child_process.spawn('ffmpeg' [
// Input
'-i', inputFile, // Use '-' to write to STDIN instead
// Set sample rate
'-ar', '44100',
// Set audio channel count
'-ac', '1',
// Audio bitrate... try to match others, but not as critical
'-b:a', '64k',
// Ensure we output an MP3
'-f', 'mp3',
// Output
outputFile // As with input, use '-' to write to STDOUT
]);
Best Solution: Let FFmpeg (or similar) do the work for you
The simplest, most robust solution to all of this is to let FFmpeg build a brand new stream for you. This will cause your audio files to be decoded to PCM, and a new stream made. You can add parameters to resample those inputs, and modify channel counts if needed. Then output one stream. Use the concat filter.
This way, you can accept audio files of any type, you don't have to write the code to hack those streams together, and once setup you won't have to worry about it.
The only downside is that it will require a re-encoding of everything, meaning another generation of quality lost. This would be required for any non-conforming files anyway, and it's just speech, so I wouldn't give it a second thought.
#Brad's answer was the solution! The first solution he suggested worked. It took some messing around getting FFMpeg to work correctly, but in the end using the fluent-ffmpeg library worked.
Each file in my case was stored on Google Cloud Storage, and not on the server's hard drive. This posed some problems for FFmpeg, as it requires file paths to have multiple files, or an input stream (but only one is supported, as there is only one STDIN).
One solution is to put the files on the hard drive temporarily, but this would not work for our use case as we may have a lot of use in this function and the hard drive adds latency.
So, instead we did as suggested and loaded each file into ffmpeg to convert it into a standardized format. This was a bit tricky, but in the end requesting each file as a stream, using that stream as an input for ffmpeg, then using fluent-ffmpeg's pipe() method (which returns a stream) as output worked.
We then bound an event listener to the 'data' event for this pipe, and pushed the data to an array (bufs.push(data)), and on stream 'end' we concatenated this array using Buffer.concat(bufs), followed by a promise resolve.
Then once all requests promises were resolved, we could be sure ffmpeg had processed each file, and then those buffers were concatenated in the required groups as before using Buffer.concat(), converted to base64 data, and sent to the client.
This works great, and now it seems to be able to handle every combination of files/sources I can throw at it!
In conclusion:
The answer to the question was that the mp3 data must have been encoded differently (different channels, sample rates, etc.), and loading it through ffmpeg and outputing it in a 'unified' way made the mp3 data compatible.
The solution was to process each file in ffmpeg separately, pipe the ffmpeg output into a buffer, then concatenate the buffers.
Thanks #Brad for your suggestions and detailed answer!
We are using PortAudio for recording audio in our electron application. As a node wrapper, we use naudiodon.
The application needs to record both audio and video, but using different sources. Audio, as said, is being recorded with Port Audio, with additional app logic on top. Video, on the other hand, is being recorded with standard MediaRecorder API, with its own formats, properties, and codecs.
We use event 'onstart' to track actual video start and in order to sync audio and video, we must also know the exact audio start time.
Problem is: We are not able to detect that exact timestamp of audio start. What should be the correct way of doing it?
Here is what we tried:
1. The first option is to listen to portaudio.AudioIO events, such as 'data' and 'readable'. Those are called as soon as PortAudio has new data chunk, so tracking the very first chunk minus its length in milliseconds would result in approximate audio start.
2. The second option is to add Writable pipe to AudioIO, and do pretty much the same thing as with events.
The issue is, that by doing any of those options, calculated start doesn't always result in the actual timestamp of audio start. While playing around with port audio it was known, that calculated timestamp is higher than it should be, as though some chunks are being buffered before actually released.
Actual audio start and first chunk release can be different, in a range of around 50 - 500 ms with chunk length ~50ms. So chunks might buffer sometimes, and sometimes they don't. Is there any way to track the actual start time of the first chunk? I wasn't able to find any relevant info in checking port audio docs.
Maybe there are any other ways to keep using PortAudio and record video separately, but finally achieve the same desired feature, of synching them together?
PortAudio 19.5, Naudiodon 2.1.0, Electron 6.0.9, Node.js 12.4.0
Say you have an MP3 file and it's 60,000,000 bytes, and you also have an MP3 advertisement that's 500,000 bytes, both encoded at the same bit rate.
Would it be possible using an nginx or apache module to change the MP3 "Content-Length" header value to 60,500,000 and then control the incoming "Content-Range" requests so the first 500,000 bytes return the advertisement audio, and any range request greater than 500,000 begins returning the regular audio file with a 500,000 byte offset?
Or is it only possible to splice advertisements (or messages) into an MP3 file using an application such as FFmpeg to re-render the entire file?
Apologies if this is a stupid question, I'm just trying to think outside of the box.
You cannot arbitrarily splice MP3 without artifacts and decoder errors.
You also generally cannot cut/splice MP3 on frame boundaries due to the Bit Reservoir. Basically, a particular MP3 frame may contain data from another frame to more efficiently use the available bandwidth when its needed. Ignoring the bit reservoir can also cause artifacts and/or decoder errors.
What you can do is re-encode your advertisement and eventually re-join the stream. That is, at the point of ad insertion, decode the stream to PCM, mix (or replace in the audio) for your ad, and have this parallel stream re-encoded to PCM. If the encoding parameters are the same, eventually (after a couple of extra MP3 frames), you'll have identical bitstreams, and you can go back to reading the stream from the same buffer.
If you're doing this for ad-insertion on internet radio (live) streams, keep in mind that you'll have to do this on the server for every client (or at least, for each ad variant and timing variant). If this is for podcasts or other pre-recorded content, I'd recommend the FFmpeg route. You won't have to build anything, you can stream and cache the output as its being encoded, and you'll have compatibility with other codecs without building one-off code for each codec/container.
Odd ball question for somebody just getting started with html5 players and streaming video....
When using YouTube long videos can be scrolled towards then end then played from there. Assuming YouTube first pulls down metadata like total video start/stop points and a bunch of thumbnails for scrolling.
Is this possible with an open html5 video player (like projekkter)? Reason asking is that I have video data inside a mongo database that I would like to stream similar to the YouTube player.
Inside mongo I have a bunch of smaller h264 files each in a document: actual raw h264 usually 1000kb (max 2 seconds), creation timestamp (long), and potentially a converted format (like mp4) for known clients. Idea is to query off a time range and order by creation time then piping the results into readable stream. There is a nice ffmpeg module to take streams and reformat if needed. Thought about piping the stream to the client with binaryjs and appending it into the player.
But the source directives in the documentation are usually URLs plus I need to lock down the start/stop point for the total video being played plus thumbnails.
For part of one of my projects, I am considering developing an audio archive for internet radio stations. This archive would be indexed and addressable by date/time.
For example, the server would connect to a stream (generally encoded in MP3), and save the stream data. A client could connect to this server and request audio from 2011-07-05 15:58:30 to 2011-07-05 15:59:37. The server would return the audio data to the client for playback.
My initial thought was to save the data to 1-minute chunks of raw MP3 data to disk, and reference these files from a database. The server would be dumb to the stream/file format, and wouldn't understand mpeg frames. It would simply pass on data to the client, dividing the chunks up linearly to send. It would be up to the client to sync to the stream. This is not unlike how internet radio servers run in general. SHOUTcast servers simply output the data, byte for byte, that is sent to them from the encoder. When a client connects, data is sent, regardless of whether or not it even ends on an MP3 frame. It is up to the client to sync.
I am wondering if there might be a better approach, maximizing compatibility with clients and audio formats. Any thoughts on how to go about this?
The only other thing I can think of is decoding the MP3 to raw PCM audio and re-encoding as necessary when requested. I would prefer not to go this route due to the disk space required, and the loss of quality when re-encoding.
This question is language-agnostic, but if it is helpful, I will likely implement a solution in PHP with MySQL as the database.
You don't have to worry about this, since ALL mp3 that I accessed over shoutcast is Constant Bitrate. Do you don't have to index it. I have POC project that had archive in 5 minute chunks, then uses PHP to combine that files and pseudo-stream it to the winamp via shoutcast. It worked!
And since you are working with mp3, you can assume (and you'll assume correctly) that the density of the captured file is linear, so to access 30 second of the 60 second file you should seek in the middle. Since mp3 decoders are robust enough, you don't have to track the frames at all here.
AACplus, whole different story. It's inherent VBR.