38 citations · 124 across the 30 of their papers we have counts for
9 papers · 1 filter
Discriminative Speech Recognition Rescoring with Pre-trained Language Models
Prashanth Gurunath Shivakumar, Jari Kolehmainen, Yile Gu +3
Second pass rescoring is a critical component of competitive automatic speech recognition (ASR) systems. Large language models have demonstrated their ability in using pre-trained…
Low-rank Adaptation of Large Language Model Rescoring for Parameter-Efficient Speech Recognition
Yu Yu, Chao-Han Huck Yang, Jari Kolehmainen +15
We propose a neural language modeling system based on low-rank adaptation (LoRA) for speech recognition output rescoring. Although pretrained language models (LMs) like BERT have s…
Personalization for BERT-based Discriminative Speech Recognition Rescoring
Jari Kolehmainen, Yile Gu, Aditya Gourav +4
Recognition of personalized content remains a challenge in end-to-end speech recognition. We explore three novel approaches that use personalized content in a neural rescoring step…
Scaling Laws for Discriminative Speech Recognition Rescoring Models
Yile Gu, Prashanth Gurunath Shivakumar, Jari Kolehmainen +3
Recent studies have found that model performance has a smooth power-law relationship, or scaling laws, with training data and model size, for a wide range of problems. These scalin…
Distillation Strategies for Discriminative Speech Recognition Rescoring
Prashanth Gurunath Shivakumar, Jari Kolehmainen, Yile Gu +3
Second-pass rescoring is employed in most state-of-the-art speech recognition systems. Recently, BERT based models have gained popularity for re-ranking the n-best hypothesis by ex…
Streaming Speech-to-Confusion Network Speech Recognition
Denis Filimonov, Prabhat Pandey, Ariya Rastrow +2
In interactive automatic speech recognition (ASR) systems, low-latency requirements limit the amount of search space that can be explored during decoding, particularly in end-to-en…
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…
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…
On-the-fly Text Retrieval for End-to-End ASR Adaptation
Bolaji Yusuf, Aditya Gourav, Ankur Gandhe +1
End-to-end speech recognition models are improved by incorporating external text sources, typically by fusion with an external language model. Such language models have to be retra…