7 citations · 10 across the 6 of their papers we have counts for
8 papers
Plan, Watch, Recover: A Benchmark and Architectures for Proactive Procedural Assistance
Kaustav Kundu, Ritvik Shrivastava, Maxim Arap +14
Proactive multimodal assistants must decide when guidance is needed and what to say, while tracking progress through extended procedures and helping users recover when they depart…
Federated Self-Learning with Weak Supervision for Speech Recognition
Milind Rao, Gopinath Chennupati, Gautam Tiwari +4
Automatic speech recognition (ASR) models with low-footprint are increasingly being deployed on edge devices for conversational agents, which enhances privacy. We study the problem…
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale
Gopinath Chennupati, Milind Rao, Gurpreet Chadha +11
Incremental learning is one paradigm to enable model building and updating at scale with streaming data. For end-to-end automatic speech recognition (ASR) tasks, the absence of hum…
On joint training with interfaces for spoken language understanding
Anirudh Raju, Milind Rao, Gautam Tiwari +6
Spoken language understanding (SLU) systems extract both text transcripts and semantics associated with intents and slots from input speech utterances. SLU systems usually consist…
Personalization Strategies for End-to-End Speech Recognition Systems
Aditya Gourav, Linda Liu, Ankur Gandhe +9
The recognition of personalized content, such as contact names, remains a challenging problem for end-to-end speech recognition systems. In this work, we demonstrate how first and…
Do as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding
Milind Rao, Pranav Dheram, Gautam Tiwari +4
Spoken language understanding (SLU) systems extract transcriptions, as well as semantics of intent or named entities from speech, and are essential components of voice activated sy…
Efficient minimum word error rate training of RNN-Transducer for end-to-end speech recognition
Jinxi Guo, Gautam Tiwari, Jasha Droppo +4
In this work, we propose a novel and efficient minimum word error rate (MWER) training method for RNN-Transducer (RNN-T). Unlike previous work on this topic, which performs on-the-…
Scalable Multi Corpora Neural Language Models for ASR
Anirudh Raju, Denis Filimonov, Gautam Tiwari +2
Neural language models (NLM) have been shown to outperform conventional n-gram language models by a substantial margin in Automatic Speech Recognition (ASR) and other tasks. There…