Speech & Audio AI

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Audio Classification Models

Audio classification models are machine learning systems for audio classification, the task of assigning one or more labels to an audio recording or to short fragments of it.

Deep Learning Machine Learning

Connectionist Temporal Classification

Connectionist temporal classification (CTC) is a loss function and output layer design for training neural networks to label unsegmented sequences, such as transcribing an audio recording into characters when…

Deep Learning Machine Learning

HuBERT

HuBERT (Hidden-Unit BERT) is a self-supervised learning model for speech representation, introduced by researchers at Meta AI (then Facebook AI Research) in 2021 .

Machine Learning

SUPERB

SUPERB, which stands for Speech processing Universal PERformance Benchmark, is a comprehensive evaluation framework designed to measure how well self-supervised learning (SSL) models generalize across a…

AI Benchmarks Machine Learning

Speech Recognition

Speech recognition, usually called automatic speech recognition (ASR), is the computational task of converting a spoken-language signal into a sequence of written symbols.

Deep Learning Machine Learning

Wav2Vec 2.0

Wav2Vec 2.0 is a self-supervised learning framework for speech representation, developed by the Facebook AI Research (FAIR) group at Meta and introduced in 2020.

Machine Learning

Word error rate

Word error rate (WER) is the standard metric for measuring the accuracy of an automatic speech recognition (ASR) system

Machine Learning Model Evaluation