Speaker recognition app using machine learning with recording and import features with GUI.
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Updated
May 30, 2024 - Python
Speaker recognition app using machine learning with recording and import features with GUI.
Champion at Brainhack TIL 2023: Team 10000SGDMRT
✍ 🗣 A Text-To-Conversation natural language processing toolkit [WIP].
An official implementation for SSAMBA: Self-Supervised Audio Mamba
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
Speaker diarization service
The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.
On-device speaker recognition engine powered by deep learning
This project performs speech recognition and diarization (speaker identification) on recordings of conversations. This is followed by sentiment analysis the transcription of each individual.
A Streamlit web application for Voice recognition using a pre-trained speech embedding model.
Backend service for extracting and processing voice data
Official implementation of the ICASSP 2024 paper: Emphasized Non-Target Speaker Knowledge in Knowledge Distillation for Speaker Verification
This repository contains audio samples and supplementary materials accompanying publications by the "Speaker, Voice and Language" team at Google.
Speakerbox: Fine-tune Audio Transformers for speaker identification.
This project was done as part of a research teaser project on Speaker Recognition conducted with IIIT Hydrabad.
Deliverables relating to the Speech Technology University Unit (Notes Courtesy to Dr. Andrea De Marco)
Recognizing and identifying Quran reciters from audio recordings.
This repository contains a short introduction on the topic of audio and speech processing -- from basics to applications.
Demo data science project to take an input utterance and predict which member of the core Rick & Morty family is most likely to say it.
Speaker identification task using deep learning models
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