Questions tagged [audio-processing]
For questions about audio processing tasks in the context of artificial intelligence.
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How is speech recognition software able to distinguish between different speakers and yet still understand them all?
Some background: I'm an EE major and data science minor, so I have a basic understanding of machine learning - I had a one semester course on it where we covered some of the most commonly used ...
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What are the differences between RVC and SO-VITS-SVC models?
I'm trying to decide which one to use for my project but I can't find anywhere specific differences or comparisons of the models.
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Feature extraction from log-mel spectrograms using CNNs
I am currently working on an ASR-related project in which I would like to combine Convolutional Neural Network with GRU Network and CTC loss function.
The idea is to use the CNN to extract ...
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How to prepare audio data for deep learning?
Audio data is typically an array with the waveform represented by values from -1 to 1. There are two issues with that:
if all values are inverted, e.g. -1 becomes 1 and 1 becomes -1, the audio doesn'...
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Training a neural network to assess audio samples that harmonize well together
I want to train a neural network that, given a set of audio samples, can determine a subset those samples that harmonize well together. The neural network should take auditory features of a set of ...
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What type of neural network architecture allows filtering out of unwanted sounds?
I have a use case where I will be inputting audio to a model, and the output of the model will be the same audio except with certain sounds removed (volume set to zero). The dataset is generated by ...
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Autoencoder make spectrogram important parts more pronounced with a "log loss"
Hi I want to create a neural network that essentially picks out the most pronounced parts of a spectrogram.
Assume this is the True spectrogram:
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How to define a loss function for multi-label problem?
I have voice recordings which are labelled by not only a single label but multiple labels. Each voice recording corresponds to one of class labels within a set. In other words, the training instance ...
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Could I cluster the audio clips in order to improve the speed of their classification?
I have a neural network which is very resource intensive and is used to classify audio clips. The classification is done in batches, where I record for a set period of time and then go through and ...
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How does using complex weights in a neural network affect performance?
If you switch a neural network from real weights to complex weights, you're roughly doubling the size of the network, and increasing the computational load by a factor of 2 to 4. My question is, in ...
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Understanding gumbel-softmax backpropagation in Wav2Vec papers
I'm studying the series of Wav2Vec papers, in particular, the vq-wav2vec and wav2vec 2.0, and have a problem understanding some details about the quantization procedure.
The broader context is this: ...
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Is it realistic to train a transformer-based model (e.g. GPT) in a self-supervised way directly on the Mel spectrogram?
In music information retrieval, one usually converts an audio signal into some kind "sequence of frequency-vectors", such as STFT or Mel-spectrogram.
I'm wondering if it is a good idea to ...
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Model for direct audio-to-audio speech re-encoding
There are many resources available for text-to-audio (or vice versa) synthesis, for example Google's 'Wavenet'.
These tools do not allow the finer degree of control that may be required regarding the ...
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Speech diarization for a conversation detector: A good idea or not?
I am trying to write a program in which an ai can detect whether a conversation is occurring or not. The ai does not need to transcribe words or have any meaning about the conversation, simply if one ...
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I want to determine how similar a given song is to Queen's songs. Am I headed in the right direction?
I've asked this question before (@ Reddit) and people suggested CNNs on a mel spectrogram more than anything else. This is great.
But I'm sort of stuck at: label some music data as "queen" ...
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How to get more accuracy of the logistic regression model?
I am working on a Baby Crying Detection model using logistic regression.
Out of $581$ audios, $222$ are of a baby crying. Each audio is of $5$ seconds.
what I have done is convert each audio into ...
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Is it likely that a sentient AI experience synesthesia?
The reason I ask this question is because we humans tend to compartmentalize our sensory inputs, except in some individuals that experience synesthesia. If an Artificial Intelligence Entity (AIE) can ...
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Can Machine Learning be used to synthesize engine sounds?
I'm working on a project to equip model locomotives with sound boards. I'm in the process of designing the board at the moment, and the idea is to allow users to load their own sound files onto an SD ...
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Can we use transformers for audio classification tasks?
Since transformers are good at processing sequential data, can we also use them for audio classification problems (same as RNNs)?
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How to combine specific CNN models that work better at slightly different tasks?
I'm not sure how to describe this in the most accurate way but I'll give it a shot.
I've developed a Inception-Resnet V2 model for detecting audio signals via spectrogram. It does a pretty good job ...
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Is there a problem for "Sound Source Identification in Video Footage"?
I've been considering starting a project for some time on sound source identification.
To be more specific, my goal is to be able to identify the "sources" for sound in videos. Moving parts ...
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How can I find a specific word in an audio file?
I'm trying to train and use a neural network to detect a specific word in an audio file. The input of the neural network is an audio of 2-3 seconds duration, and the neural network must determine ...
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What is the most compressed audio that I can feed an AI?
The problem I currently have is that I want to train an AI to produce music, like music that contains voices etc... However, the problem is that with a WAV file, one second of audio can be up to 48,...
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What are the best datasets available for music information retrieval?
I am interested in doing some work in classification problems in music information retrieval. I know that there are some formats of datasets (such as MIDI, Spectrogram, Piano-roll, MusicXML, etc.) for ...
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Is there an AI that can complete Deezer Spleeter work?
I have used Deezer Spleeter but it produces echoes aside the stems, so I wonder if there is already an AI that remove echoes noises.
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Noise Cancellation on live audio stream
I want to build an application which takes a live audio from source (mic) and filtering the noise (unwanted sounds like chattering, traffic noises) and fetch into an application for further processing....
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How do I train a multiple-speaker model (speech synthesis) based on Tacotron 2 and espnet?
I'm new to Speech Synthesis & Deep Learning. Recently, I got a task as described below:
I have problem in training a multi-speaker model which should be created by Tacotron2. And I was told I can ...
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State of the art in voice recognition
In the media there's lot of talk about face recognition, mainly with respect to identifying faces (= assigning to persons). Less attention is paid to the recognition of facially expressed emotions but ...
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How to use AI for language recognition?
Given an audio track, I'm trying to find a way to recognize the audio language. Only within a small set (e.g. English vs Spanish). Is there a simple solution to detect the language in a speech?
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Deep audio fingerprinting for word search
Simply speaking, I'm trying to somehow search an audio clip for a list of words, and if found, I mark the time stamps. My use-case is profanity check with a list of pre-defined profane words.
Is ...
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Can AI be used to reverse engineer a black box?
A while back I posted on the Reverse Engineering site about an audio DSP system whose designer had passed away and whose manufacturer no longer had source code (but the question was deleted). ...
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Speech to text models [closed]
I'm currently using google speech to text api to transcribe audio in real time (police scanner audio dispatches). The audio quality isn't great and I've been putting in key words to try to help train ...
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What are the current open source text-to-audio libraries? [closed]
I am not new to AI and did some work for few months but completely new to text to audio. Yes I used text to audio tools a decade back... but I would like to know where exactly we stand in terms of ...
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Isolate the speech of two people in an audio record with two people only
I would like to find a way to isolate the speech of each of the people in an audio record so I can create a file of that form :
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Can I filter barking sounds on the television? [closed]
My dog goes bonkers every time the sound of a barking dog is heard on a television program. I never noticed this before but literally every movie or show with an outdoors setting eventually includes ...
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Is it possible to clean up an audio recording of a lecture using some type of AI system?
Is it possible to clean up an audio recording of a lecture from a smartphone (i.e. remove the background noise) using some type of AI system?
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How to combine input from different types of data sources?
I've to train a neural network using microphone data (wav files), accelerometer sensor data and light sensor data.
Right now the approach I thought was to convert all data into images and combine ...
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Difficulty understanding Keras LSTM fitting data
I'm try to train a RNN with a chunk of audio data, where X and Y are two audio channels loaded into numpy arrays. The objective is to experiment with different NN designs to train them to transform ...
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