Cette application utilise la reconnaissance vocale , la synthèse vocale et la reconnaissance du locuteur
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Updated
Feb 2, 2020 - Java
Cette application utilise la reconnaissance vocale , la synthèse vocale et la reconnaissance du locuteur
This project is about the analysis of different audio files in order to compute the ”speaker recognition task”,
The Additive Margin MobileNet1D is a new light weight deep learning model for Speaker Recognition which is based on the MobileNetV2 architecture and the Additive Margin Softmax (AM-Softmax) loss function.)
ReactJs application helping user to get quick headlines news from all around the globe and with a personlized features such as country ,categories ,sources and with speaker recognition experience
Contains the code relevant to my Master's Thesis at the City College Of New York on Edge Device Text-Independent Speaker Recognition.
Plot Detection Error Trade-off, False Acceptance Rate vs False Rejection Rate, Receiver Operating Characteristic
Russian Spontaneous Speech Data
This is a project that demonstrates the use of python speech recognition to help control any sort of game.
In defence of metric learning for speaker recognition, test on voxceleb1 eer=2.21%
A high-performance (98% identification accuracy) & low-cost industrial speaker identification system.
Speaker recognition for flexible throat microphone viacontrastive learning
3 different tasks of processing of digital signals where performed by using deep learning. (Speaker recognition, Face recognition, Image retrieval))
Korean Spontaneous Speech Data
Hindi Spontaneous Speech Data
Latin American Spanish Child's Spontaneous Speech Data
Visual speaker recognition method using HMM for classification and regression trees for features extraction
This is a speaker verification system uses Total Variability and Projection Matrix. Intersession variability was compensated by using backend procedures, such as linear discriminant analysis (LDA) and within-class covariance normalization (WCCN), followed by a scoring, the cosine similarity score. In literature this approach named i-vectors.
This is a ros package for voice recognition and uses wit.ai for speech analysis.
Speaker Recognition deep learning model based on feature extraction from Mel Frequency Cepstral Coefficients. Solution code for Signal Processing Cup 2024.
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