Can someone please tell me if it is possible to make speaker recognition using tensorflow? I am extracting MFCC data from audio file using librosa and by that I want to recognize speaker. Any suggestions or links on how to implement that?
Check this repo -> https://github.com/pannous/tensorflow-speech-recognition
You can view the speaker_classifier_tflearn.py and get a feeling on how it works.
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I am using just_audio, an amazing Flutter package that helps us working with .mp3 files.
The thing is... I need to compare 2 audios for creating a Tunner (Voice Tunner to be specific). I am using frequencies in the audios to compare.
FFT helps us to separate the frequencies from the audio.
In just_audio it has a feature, called FFT (beta). However, I couldn't figure it out how to use it. I was wondering if somebody have any tips to help me understanding it.
Thank you!
I have a music file with a particular tone(music.mp4). I want to convert existing sound file (speech.mp4) into the tone which is specified in music.mp4. Its like converting a speech into some particular tone. I do not want to play both files simultaneously. I want to convert source file with help of some music file. So, output file will be converted file.
Is it possible? I searched for Audio Unit Hosting and Multimedia guide. But do not get any clue.
Thanks in advance.
The answer is: it sounds (no pun intended) like it would be possible with the iOS. You just need to find someone who knows how to program that specific functionality. I do not know why you would think to find the answer in the Apple Docs. I want to know if it's possible to program music that plays backwards. I want to know if I can program a sound that converts my words into something my dog understands. I can't imagine the documentation could possibly cover everything everyone ever wants to program an iPhone to do.
There are no iOS public APIs for frequency analysis of audio files. You would have to write your own DSP code for that. The AVFoundation and Accelerate frameworks have some audio file conversion and math functions that may help, but that is only a small portion of the code needed.
I'm looking a way to find the BPM of a song stored in the iphone library wuthout playing it. I'm not experienced on that, anyone can confirm me that it's possible?
I have never used it, but here's an open source c++ beat detection library you could try:
http://sourceforge.net/projects/beatdetektor/
Possibly. The AVFoundation framework and AVAssetReader can be used to convert library music into raw waveform data. You could try writing a DSP spectral envelope follower and do an autocorrelation on the envelopes to estimate the BPM.
If anyone's running into this problem today... I made a github repo which shows how you can grab bpm of a local audio file.
https://github.com/yaizudamashii/BPMDetection-iOS
In my app,i need to generate video with audio. Now i am using Air Play Sample But its contains only generate video only and i need to generate video with audio.Any one help me to solve with problem.
Regards,
First of all, you need to increase your accept rate.
Secondly, this is quite a lot what you are asking for. I'm not familiar with Air Play, but my suggestion would be to start with the SpeakHere project. That will get you familiarised with core-audio and give you a template for accessing the audio input.
As for the visual aspect I highly recommend O'Reilly's 3D Programming book which provides a lot of example code.
It will take a bit of time to assimilate both materials, but you'll end up with a better application.
I am currently working on an App which needs to get some data from the microphone. I have read through some resources on the Internet and believe that Audio Queue is a good library to do it.
I only need to get an array which stores the microphone input data, and do not need to play it back.
Can anyone kindly give some hints on that? Greatly appreciated if a simple sample/essential code fragments can be given.
Speak Here App given by the Apple can give you some idea.You can get the link here http://developer.apple.com/iPhone/library/samplecode/SpeakHere/index.html