jupyter notebooks to fine tune whisper models on Vietnamese using Colab and/or Kaggle and/or AWS EC2
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Updated
Apr 14, 2024 - Jupyter Notebook
jupyter notebooks to fine tune whisper models on Vietnamese using Colab and/or Kaggle and/or AWS EC2
Whisper AI is an automated speech recognition (ASR) system. It is open source and can be access via GitHub or HuggingFace. This is the simplest way to implement Whisper AI via Github using python Google Colab Notebook.
The GitHub repository focuses on transforming audio files into mel-spectrogram images. It was created for the "UrbanSound8k Mel Spectrogram Images" dataset on Kaggle. Key features include sound visualization and dataset creation for sound analysis. The repository includes an Audio-to-Spectrogram.ipynb notebook for creating spectrograms.
This repository provides a Jupyter notebook for (CTC) based Automatic Speech Recognition (ASR) system using TensorFlow and Keras. The primary focus of this repository is to demonstrate the implementation of a CTC ASR model and to show how to train it effectively on the "Yes No" dataset.
In this notebook, we are recognizing digits from 0 to 9 based on audio recordings file. Input data will be in the form of speech signal and output will be a single digit.
A speech emotion recognition notebook that learns a model to identify the emotion within human speech with an accuracy of roughly 60%.
In this notebook, I implemented a script to transcribe YouTube videos (and audio files in general) using Google's speech-to-text API.
💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️
✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a HEARING PROXIA (B) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
ready to use notebook to finetune wav2vec2 on persian
In this notebook, we will create to convert an audio file of an English speaker to text using a Speech to Text API using IBM-Watson. Then we will translate the English version to a Spanish version using a Language Translator API.
Simple Jupyter Notebook including a Speech Recognition implementation with CMUSphinx
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