7 votes

Is it possible to clean up an audio recording of a lecture using some type of AI system?

Yes, it is possible. Usually, the noise reduction is done using regular signal processing methods, such as spectral subtraction due to demand for low latency. But, of course, modern methods of deep ...
  • 171
3 votes
Accepted

Is it realistic to train a transformer-based model (e.g. GPT) in a self-supervised way directly on the Mel spectrogram?

The reason most music-generation models use discrete representations is because the long-term structures of music are very challenging to model. Note that the MIDI data in MAESTRO (used in the two ...
  • 194
3 votes

How to get more accuracy of the logistic regression model?

Try Rectification Improve the features available to your model, Remove some of the NOISE present in the data. In audio data, a common way to do this is to smooth the data and then rectify it so that ...
  • 625
2 votes

How can I find a specific word in an audio file?

After some research on the internet, I realized that using VOSK toolkit in python, it can be found (detect) any particular word in audio file or real time audio streaming. https://alphacephei.com/vosk/...
2 votes

I want to determine how similar a given song is to Queen's songs. Am I headed in the right direction?

You are heading in the right direction to make an audio-based classifier. This is not quite the same as providing a similarity metric between two pieces of audio, but it may do as a first attempt. You ...
  • 24.6k
1 vote
Accepted

How to define a loss function for multi-label problem?

Given your response in the comments, you are faced with a semi-supervised learning problem where you have a small set of data with ground truth labels, and a large set of data without ground truth ...
1 vote

How to define a loss function for multi-label problem?

If I understand correctly, the training data are voice messages which contain one or more suggested labels for the class that the voice message belongs to. Even though there are multiple suggestions, ...
  • 21
1 vote

Is it realistic to train a transformer-based model (e.g. GPT) in a self-supervised way directly on the Mel spectrogram?

These papers are also very close to what I meant in the question (too long for a comment). The following references come mostly from work on speech recognition. Mockingjay In this work, they use an ...
1 vote
Accepted

Can we use transformers for audio classification tasks?

Yes, Transformers can be used to work with audio data, such as audio processing (audio classification, speaker identification, etc) (Audio ALBERT), speech-to-text (Streaming Automatic Speech ...
  • 1,260
1 vote

Difficulty understanding Keras LSTM fitting data

Yes, intuition says that RNNs like LSTM or GRU will work better in your case, because predicted values might depend on input patterns corresponding to much earlier time intervals. There is no reason ...
  • 21
1 vote

How to use AI for language recognition?

Google has an API you can use. https://cloud.google.com/translate/. Their API can translate audio to text. They also have an API for converting speech to text. The language detection feature should ...
  • 182
1 vote

Deep audio fingerprinting for word search

You would need to perform some kind of speech-to-text to get the audio transcription with the corresponding synchronization wrt the audio. Then search in the ...
1 vote

Can AI be used to reverse engineer a black box?

Yes this is entirely possible. As was previously mentioned, complex connectionist systems are often thought of as black boxes(despite us being able to "look in" the box given enough computation and ...
1 vote

What are the current open source text-to-audio libraries?

voice-builder is an opensource text-to-speech (TTS) voice building tool from Google.
1 vote

Isolate the speech of two people in an audio record with two people only

The task of isolating 2 or more speakers is called speaker diarization, here a list of softwares and useful resources. Once you have the 2 or more audio files ...
1 vote

Can I filter barking sounds on the television?

OK, here is one approach. Acquire a data set of 'clean' audio samples without barking dogs and an data set of barking dogs sounds. Generate a training set by mixing random selections of clean audio ...
  • 583

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