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• How to stop a sound when certain other sound is inserted in the mix in ffmpeg ?

  3 avril 2022, par Antonio Oliveira

  I'm using a ffmpeg command that takes a set of sounds, mixes them into a single file, separating them by certain time intervals.

  


  Below is how my command is today.

  


  ffmpeg -i 
close_hh.wav    -i \
crash_l.wav     -i \
crash_r.wav     -i \
floor.wav       -i \
kick_l.wav      -i \
kick_r.wav      -i \
open_hh.wav     -i \
ride.wav        -i \
snare.wav       -i \
splash.wav      -i \
tom_1.wav       -i \
tom_2.wav       -i \
  tom_3.wav  -filter_complex  " [6]adelay=0|0[note_0];  [0]adelay=360|360[note_1];  [6]adelay=1260|1260[note_2];  [0]adelay=1537|1537[note_3];  [6]adelay=2494|2494[note_4];  [5]adelay=2767|2767[note_5];  [0]adelay=2969|2969[note_6];  [6]adelay=3673|3673[note_7];  [5]adelay=3924|3924[note_8];  [0]adelay=4132|4132[note_9];  [0][note_0][note_1][note_2][note_3][note_4][note_5][note_6][note_7][note_8][note_9]amix=inputs=11:normalize=0" record.wav


  


  This is the resulting audio that this command generates :

  


  ffmpg record.wav : https://drive.google.com/file/d/1LFV4ImLKLnRCqZRhZ7OqZy4Ecq5fwT3j/view?usp=sharing

  


  The purpose is to generate a drum recording, so I would like to simulate the dynamics of the hi-hat sounds : When the closed hi-hat is played, the open hi-hat will stop playing immediately if it is still sounding. The same behavior does not happen for any of the other sounds.

  


  One point that makes this a little more challenging is that other sounds can also be played between open hi-hat and closed hi-hat strikes, and theoretically the sound interruption behavior should work normally.

  


  Below is a recording demonstrating the expected result. (My app already reproduces the sound result I need internally, so I just made a simple recording with the microphone to illustrate)

  


  mic record.wav https://drive.google.com/file/d/19x19Fd_URQVo-MMCmGEHIC1SjaQbpWrh/view?usp=sharing

  


  Notice that in the first audio (ffmpeg record.wav) the first sound (open hi-hat) continues playing after the second is played.
In the second audio (mic record.wav) the first sound stops immediately after the second sound is played.

  


  How should the ffmpeg command be to get the expected result ?

  


• Normalizing with ffmpeg-normalize, slight variations in sound

  20 mai 2022, par Antti Rytsölä

  I have some flacs which I am trying to normalize for Spotify and Distrokid.

  


  I got the guide from this post

  


  ffmpeg-normalize inbound/*.flac -t -14 -lrt 11 -tp -1 -ext flac -c:a flac -of normalized/


  


  Now the problem is ( before submitting to Distrokid ) that when listening to normalized versions there seems to be light deviations, like muffling, to the sound at half a second lenghts.

  


  Small sample, towards the end.

  


  Now I'm asking for help because even though I can try different settings I still want to conform to Spotify normalization guide.

  


  The Spotify guide is as follows :

  


  Target the loudness level of your master at -14dB integrated LUFS 
and keep it below -1dB TP (True Peak) max. This is best for lossy 
formats (Ogg/Vorbis and AAC) and makes sure no extra distortion’s 
introduced in the transcoding process.

If your master’s louder than -14dB integrated LUFS, make sure 
it stays below -2dB TP (True Peak) to avoid extra distortion. This 
is because louder tracks are more susceptible to extra distortion 
in the transcoding process.


  


  and

  


   ffmpeg version N-102727-g580e168a94-tessus
 ffmpeg-normalize v1.22.8


  


  Tracks now on Spotify.

  


• I tried to play the audio on Alexa skill from my S3 Bucket, from the test tab, **it show but in fact, I can't hear any sound

  19 avril 2022, par Siti Mayna

  So I tried to play the audio on Alexa skill from my S3 Bucket, from the test tab, it show but in fact, I can't hear any sound. Another fact is, that I tried to use the sample audio from https://developer.amazon.com/en-US/docs/alexa/custom-skills/ask-soundlibrary.html and it is worked, but why it won't work when it comes from my own S3 Bucket ?

  


  Notes :

  


  I've tried to test the skill using my mobile phone also.

  


  I've tried to encode the audio using FFmpeg.

  


  I've tried to use Jovo to convert the audio. https://v3.jovo.tech/audio-converter

  


  I don't know how to fix this error.

  


  There is no error message on cloud watch.

  


  Assumptions :
There is some problem related to the audio resources or there is more set to play audio from S3 Bucket since the sample audio is working.

  


  Steps to reproduce :

  


  


  Build the interaction model

  


  


  


  Encode the audio to make it Alexa skill friendly (fulfill the requirements, like sample rate, etc), I used and tried all of these :

  


  


  A :

  


  ffmpeg -i  -ac 2 -codec:a libmp3lame -b:a 48k -ar 16000 -write_xing 0 


  


  B :

  


  ffmpeg -i  -ac 2 -codec:a libmp3lame -b:a 48k -ar 24000 -write_xing 0 


  


  C :

  


  ffmpeg -y -i input.mp3 -ar 16000 -ab 48k -codec:a libmp3lame -ac 1 output.mp3


  


  


  Upload the audio resources on S3Bucket
Audio sample on s3 storage but none of them are produce any sounds

  


  


  


  Use the link and insert it to APLA.json

  


  


  
    {
      "type": "APLA",
      "version": "0.91",
      "description": "Simple document that generates speech",
      "mainTemplate": {
        "parameters": [
          "payload"
        ],
        "type": "Sequencer",
        "items": [
          {
            "type": "Audio",
            "source": "https://72578561-d9d8-47b4-811c-cafbcbc5ddb9-us-east-1.s3.amazonaws.com/Media/one-small-step-alexa-24.mp3"
          }
        ]
      }
    }



  


  notes : I change the link sources based on audio that I tried.

  


  


  the intent on lambda_function.py :

  


  


  def _load_apl_document(file_path):
    # type: (str) -> Dict[str, Any]
    """Load the apl json document at the path into a dict object."""
    with open(file_path) as f:
        return json.load(f)

class LaunchRequestHandler(AbstractRequestHandler):
    """Handler for Skill Launch."""
    def can_handle(self, handler_input):
        # type: (HandlerInput) -> bool

        return ask_utils.is_request_type("LaunchRequest")(handler_input)

    def handle(self, handler_input):
        # type: (HandlerInput) -> Response
        logger.info("In LaunchRequestHandler")

        # type: (HandlerInput) -> Response
        speak_output = "Hello World!"
        # .ask("add a reprompt if you want to keep the session open for the user to respond")

        return (
            handler_input.response_builder
                #.speak(speak_output)
                .add_directive(
                        RenderDocumentDirective(
                            token="pagerToken",
                            document=_load_apl_document("APLA.json"),
                            datasources={}
                        )
                    )
                .response
        )


  


  


  Deploy

  


  


  


  Test it

  


  


  


  The result of the test on my end :

The response for testing

  


  


  the JSON response :

  


  {
    "body": {
        "version": "1.0",
        "response": {
            "directives": [
                {
                    "type": "Alexa.Presentation.APLA.RenderDocument",
                    "token": "pagerToken",
                    "document": {
                        "type": "APLA",
                        "version": "0.91",
                        "description": "Simple document that generates speech",
                        "mainTemplate": {
                            "parameters": [
                                "payload"
                            ],
                            "type": "Sequencer",
                            "items": [
                                {
                                    "type": "Audio",
                                    "source": "https://72578561-d9d8-47b4-811c-cafbcbc5ddb9-us-east-1.s3.amazonaws.com/Media/one-small-step-alexa-24.mp3"
                                }
                            ]
                        }
                    },
                    "datasources": {}
                }
            ],
            "type": "_DEFAULT_RESPONSE"
        },
        "sessionAttributes": {},
        "userAgent": "ask-python/1.16.1 Python/3.7.12"
    }
}


  


  


  On my cloud Watch :
Cloud Watch