Acoustic Modelling
12 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Acoustic Modelling
SALMon
Most implemented papers
End-to-End Attention-based Large Vocabulary Speech Recognition
Many of the current state-of-the-art Large Vocabulary Continuous Speech Recognition Systems (LVCSR) are hybrids of neural networks and Hidden Markov Models (HMMs).
WGANSing
MTG/WGANSing
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Interspeech 2019
We present a deep neural network based singing voice synthesizer, inspired by the Deep Convolutions Generative Adversarial Networks (DCGAN) architecture and optimized using the Wasserstein-GAN algorithm.
GIBBONFINDR: An R package for the detection and classification of acoustic signals
The recent improvements in recording technology, data storage and battery life have led to an increased interest in the use of passive acoustic monitoring for a variety of research questions.
Acoustic Model Adaptation from Raw Waveforms with SincNet
Raw waveform acoustic modelling has recently gained interest due to neural networks' ability to learn feature extraction, and the potential for finding better representations for a given scenario than hand-crafted features.
Multilingual Bottleneck Features for Improving ASR Performance of Code-Switched Speech in Under-Resourced Languages
In this work, we explore the benefits of using multilingual bottleneck features (mBNF) in acoustic modelling for the automatic speech recognition of code-switched (CS) speech in African languages.
Fireball characteristics derivable from acoustic data
Near field acoustical signals from fireballs (ranges<200 km), when detected by dense ground networks, may be used to estimate the orientation of the trajectory of a fireball (Pujol et al., 2005) as well as fragmentation locations (Kalenda et al., 2014; Edwards and Hildebrand, 2004).
Common Phone: A Multilingual Dataset for Robust Acoustic Modelling
MaloMn/wav2vec2-phone-classification
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LREC 2022
A Wav2Vec 2. 0 acoustic model was trained with the Common Phone to perform phonetic symbol recognition and validate the quality of the generated phonetic annotation.
Matcha-TTS: A fast TTS architecture with conditional flow matching
We introduce Matcha-TTS, a new encoder-decoder architecture for speedy TTS acoustic modelling, trained using optimal-transport conditional flow matching (OT-CFM).
