11 citations · 17 across the 6 of their papers we have counts for
7 papers
Responsible ASR: Overcoming Challenges of Foundational Models in Narrow-Band and Low-Resource Settings
Tejas Godambe, Nutan Choudhary, Sanket Shah +2
Telephony conversations worldwide are conducted over narrow-band channels and are often spontaneous and colloquial in nature. This paper evaluates the performance of widely used fo…
Synergistic Effects of Knowledge Distillation and Structured Pruning for Self-Supervised Speech Models
Shiva Kumar C, Jitendra Kumar Dhiman, Nagaraj Adiga +1
Traditionally, Knowledge Distillation (KD) is used for model compression, often leading to suboptimal performance. In this paper, we evaluate the impact of combining KD loss with a…
On the compression of shallow non-causal ASR models using knowledge distillation and tied-and-reduced decoder for low-latency on-device speech recognition
Nagaraj Adiga, Jinhwan Park, Chintigari Shiva Kumar +4
Recently, the cascaded two-pass architecture has emerged as a strong contender for on-device automatic speech recognition (ASR). A cascade of causal and shallow non-causal encoders…
Context-based out-of-vocabulary word recovery for ASR systems in Indian languages
Arun Baby, Saranya Vinnaitherthan, Akhil Kerhalkar +3
Detecting and recovering out-of-vocabulary (OOV) words is always challenging for Automatic Speech Recognition (ASR) systems. Many existing methods focus on modeling OOV words by mo…
Non-native English lexicon creation for bilingual speech synthesis
Arun Baby, Pranav Jawale, Saranya Vinnaitherthan +3
Bilingual English speakers speak English as one of their languages. Their English is of a non-native kind, and their conversations are of a code-mixed fashion. The intelligibility…
A non-causal FFTNet architecture for speech enhancement
Muhammed PV Shifas, Nagaraj Adiga, Vassilis Tsiaras +1
In this paper, we suggest a new parallel, non-causal and shallow waveform domain architecture for speech enhancement based on FFTNet, a neural network for generating high quality a…