Questions tagged [speech-to-text]
The speech-to-text tag has no usage guidance.
43
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Adding words to vocabulary on pre-trained ASR model
I have a pre-trained ASR model but want to add some missing words to the vocabulary. Can I do this or will it invalidate the entire training?
Lets say I use the pretrained model: wav2vec2-base-960h ...
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15
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Using synthetic dataset for training NVIDIA NeMo Matchbox
Does anyone has success in training small command recognition models on synthetic dataset?
The full details is the following: I need a small model to run a command recognition (about 30 commands) on ...
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Difference between speech recognition and automatic speech recognition
I was wondering, is there a difference between Speech Recognition and Automatic Speech Recogntion? I have seen both terms used in various papers, and I am not sure whether they are simply used ...
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NameError: name 'librosa' is not defined [closed]
i'm working on Arabic Speech Recognition using Wav2Vec XLSR model.
While fine-tuning the model it gives the error shown in the picture below.
i can't understand what's the problem with librosa it's ...
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How can I build my voice speech-to-text model?
I found an instruction to build such kind of custom model on Azure.
Prepare data for Custom Speech
However, I would like to either fine-tune or transfer learning on Google Colaboratory or docker.
In ...
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20
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Evaluate Text-to-speech without Human Involved?
I've explored text-to-speech evaluation matrices and they seem to used Mean Opinion Score (MOS) to evaluate a particular model. This matrice required humans to help to judge the model based on a scale ...
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58
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NeMo Conformer-CTC Predicts Same Word Repeatedly When Fine-Tuning
I'm using the NeMo Conformer-CTC small on the LibriSpeech dataset (the clean subset, around 29K inputs, using 90% for training and 10% for testing). I use Pytorch Lightning.
When I try to train, the ...
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33
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How Pretraining part actually work in Wav2vec models? Which data is qualify to be the adequat for fine-tuning part the model of speech2text
Pretraining and fine-tuning the algorithm of wav2vec2.0, the new one using in FAcebookAI to do speech to text for low-resource language.
I didn't actually get how the model does the pretraining part ...
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21
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How to train my model on unpaired speech and text for my speech recognition model?
When we have unpaired data, means we have a dataset of audios and a dataset of texts, BUT they are not associated, and as we know, to build a speech recognition model we do have to combine in our ...
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32
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Hidden Markov models in Speech Recognition
My first question here. So I am trying to build a sign language translator(from signs to text) and noticed that the problem itself is quite similar to speech recognition, so I started to research ...
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What are the hidden and observed states when building an acoustic model?
I have been trying to learn how to build ASRs and have been researching for awhile now, but I can't seem to get a straight answer. From what I understand, an ASR requires an Acoustic Model. That ...
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How to double audio dataset?
I am trying to develop a mispronunciation detection model for English speech. I use TIMIT dataset, this is phoneme labeled audio dataset.
A phoneme is any of the perceptually distinct units of sound. ...
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How do I initialize a Hidden Markov Model when using MFCC features for speech recognition?
I have a personal dataset of 10000 audio files, each consisting a single spoken sentence. These files each have the transcribed text labels with them that I can use for supervised HMM training.
Now ...
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215
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How does Wav2Vec 2.0 feed output from Convolutional Feature Encoder as input to the Transformer Context Network
I was reading the Wav2Vec 2.0 paper and trying to understand the model architecture, but I have trouble understanding how audio raw inputs of variable lengths can be fed through the model, especially ...
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31
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How to build a speech corpus for continuous speech?
I am developing a speech corpus from audiobooks. I was able to collect recordings with their transcriptions but without timing information. Therefore I am looking for recent techniques to ...
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How to evaluate the quality of speech-to-text data without access to the true labels?
I am dealing with a data set of transcribed call center data, where customers are being recorded when interacting with the agent. This is then automatically transcribed by an external transcription ...
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How to do phoneme segmentation using dynamic time warping?
Background Information:
Dynamic Time Warping (DTW):
In time series analysis, dynamic time warping (DTW) is one of the
algorithms for measuring similarity between two temporal sequences,
which may ...
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43
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How is an ASR's output compared to ground truth for validation?
I am curious how it is done as I am interested in doing something similar. I have some manually transcribed data that contains tags for multiple speakers. I want to compare how well the out of the box ...
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35
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About building database for persian speech to text project [closed]
In connection with the persian speech to text project on github, I am trying to collect the database from the audio and text available on the ganjoor site and Youtube Persian videos with Persian ...
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2k
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AttributeError: 'Functional' object has no attribute 'uses_learning_phase'
I am trying to predict on my test set and I get the following error
AttributeError: 'Functional' object has no attribute 'uses_learning_phase'
The model is created ...
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218
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How to change voice features in python without affecting speech/language features?
I am trying to build a CNN model which should be able to identify the language being spoken in an audio file. I have extracted the MFCC matrix (for 13 coefficients) for each audio file and trained it....
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208
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How to prepare Audio-text data for speech recognition
I have gathered some raw audio from all the conferences, meetings, lectures & casual conversation that I was part of. The machine transcription did not offer good results (from Azure, AWS etc.) I ...
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633
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ValueError: Error when checking input: expected the_input to have 3 dimensions, but got array with shape (14174, 1)
hope you're all doing good !
I am working on Automatic Speech Recognition with Python with the LibriSpeech Dataset.
After preprocessing the audios data and applying an "MFCC featurizing" I ...
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How to make sense of the input and output for a speech-generation model like WaveNet?
I am currently studying this model speech generation known as WaveNet model by Google. https://arxiv.org/pdf/1609.03499.pdf using the linked original paper and this implementation.
I find the model ...
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Inconsistency on A. Graves' original Connectionist Temporal Classification (CTC) paper?
Here's the link to the paper.
For the forward-backward algorithm, they introduce $\alpha_t(s)$ as a definition in eq. (5).
Then they give a recursive formula for it (eq. (6)), and its initialization. ...
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20
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Split text into phrases of a person and an operator
I have about 5,000 texts without punctuation marks.
Each text is a conversation between an operator and a person.
For example: "Hello hello how can I help you how can I find out how much money I have ...
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97
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Conv1D specify output chanels in tensorflow 2.1
Hello I'm trying to implement the "Tacotron Towards end to end" paper and in the
Encoder CBHG - a Conv1D bank of K=16, conv-k-128-ReLU
“conv-k-c-ReLU” - denotes 1-D ...
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1
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35
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Detection of anomal data in the text
I work with texts where there is a dialogue between two people (a client and a call center employee, the beginning and end of each person’s phrase is not defined). My goal is to classify texts in ...
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42
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Why gaussian assumption in GMM-HMM ASR?
I am reading a book entitled Speech and Language Processing by Daniel Jurafsky and James.
For Acoustic vector, I would like to know why Gaussian assumption is made?
I searched over the internet and ...
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196
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Creating pronunciation dictionary for ASR
I am working on ASR(automatic speech recoginition) on Somali data as master thesis and now I am stuck with how to create a phonetics or pronunciation dictionary for it. I searched over net and could ...
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88
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GMM in speech recoginition using HMM-GMM
I am trying to solve/understand ASR using HMM-GMM.
At the abstract level i do understand what's happening but I did not
understand how GMM fits into it.
My data has 5K hours of speech from single ...
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189
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ASR on low dataset
I am doing an ASR(automatic speech recognition) as master thesis on low key dataset. Voice and text data is labelled. There are around 4000 phrases and around 5 hours speech.
I don't have background ...
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116
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where to start in natural language processing for a language
My native language is a regional language and few people speak it. I have some assignements in a machine learning course and i was thinking about doing some natural languge processing on my native ...
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313
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Training an acoustic model for a speech-to-text engine
What are the steps for training an acoustic model? The format of the data (the audio) includes its length and other characteristics. If anyone could provide a simple example of how to train an ...
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42
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What to use in setting up a Speech to Text engine in production?
So i have the task to study the feasability of setting up a Speech-To-Text engine in a production environnement, and i've been researching on this topic, so I tried Google's Speech-To-Text API and ...
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135
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Segment 5-7 min audio into sentence wise audio clips for creating speech recognition dataset
I am trying to create a speech recognition dataset, especially for Indian Accents.
I am taking from colleagues to build this.
Daily I send an article link and ask them to record and upload it to ...
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69
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Can I create a good Speech Recognition Engine while having millions of recorded conversations?
I have at my disposal millions of wav files containing recorded conversations between employees and clients, i'm doing some research on the possibility of creating a good speech recognition engine. I'...
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44
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Opensource Speech Recognition Library that is secure and trained on large data [closed]
For all those who are working on developing a chatbot/assistant and care about the privacy of users consuming the speech recognition library, can you suggest an open souce library which is trained on ...
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Why are observation probabilities modelled as Gaussian distributions in HMM?
HMM is a statistical model with unobserved (i.e. hidden) states used for recognition algorithms (speech, handwriting, gesture, ...). What distinguishes DHMM form CHMM is the transition probability ...
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Representing output label for character level speec recognition using RNN
I saw this tutorial on generating text using LSTM. In this tutorial the author trained the network by taking 100 previous characters as input and the next character as the output label.
I am ...
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1
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400
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Validation loss is less than training loss by 5 units. How this result is interpreted?
Iam training a Keras model for end-to-end speech recognition. I have my own dataset of speech containing about 400 wave files. Text transcriptions is also given as input. Model summary is:
...
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How to convert a mel spectrogram to log-scaled mel spectrogram
I was reading this paper on environmental noise discrimination using Convolution Neural Networks and wanted to reproduce their results. They convert WAV files into log-scaled mel spectrograms. How do ...
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333
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How can I create a space in IBM Cloud?
I want to try the IBM speech to text API. I created an IBM cloud account and went to https://console.bluemix.net/catalog/services/speech-to-text. I see the error message:
Please create a space in ...
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