14 citations · 24 across the 20 of their papers we have counts for
7 papers · 1 filter
Search Optimization with Query Likelihood Boosting and Two-Level Approximate Search for Edge Devices
Jianwei Zhang, Helian Feng, Xin He +3
We present a novel search optimization solution for approximate nearest neighbor (ANN) search on resource-constrained edge devices. Traditional ANN approaches fall short in meeting…
Accelerator-Aware Training for Transducer-Based Speech Recognition
Suhaila M. Shakiah, Rupak Vignesh Swaminathan, Hieu Duy Nguyen +6
Machine learning model weights and activations are represented in full-precision during training. This leads to performance degradation in runtime when deployed on neural network a…
Robust Acoustic and Semantic Contextual Biasing in Neural Transducers for Speech Recognition
Xuandi Fu, Kanthashree Mysore Sathyendra, Ankur Gandhe +4
Attention-based contextual biasing approaches have shown significant improvements in the recognition of generic and/or personal rare-words in End-to-End Automatic Speech Recognitio…
Lookahead When It Matters: Adaptive Non-causal Transformers for Streaming Neural Transducers
Grant P. Strimel, Yi Xie, Brian King +3
Streaming speech recognition architectures are employed for low-latency, real-time applications. Such architectures are often characterized by their causality. Causal architectures…
Dual-Attention Neural Transducers for Efficient Wake Word Spotting in Speech Recognition
Saumya Y. Sahai, Jing Liu, Thejaswi Muniyappa +8
We present dual-attention neural biasing, an architecture designed to boost Wake Words (WW) recognition and improve inference time latency on speech recognition tasks. This archite…
Dialog act guided contextual adapter for personalized speech recognition
Feng-Ju Chang, Thejaswi Muniyappa, Kanthashree Mysore Sathyendra +3
Personalization in multi-turn dialogs has been a long standing challenge for end-to-end automatic speech recognition (E2E ASR) models. Recent work on contextual adapters has tackle…
PROCTER: PROnunciation-aware ConTextual adaptER for personalized speech recognition in neural transducers
Rahul Pandey, Roger Ren, Qi Luo +7
End-to-End (E2E) automatic speech recognition (ASR) systems used in voice assistants often have difficulties recognizing infrequent words personalized to the user, such as names an…