9 citations · 24 across the 7 of their papers we have counts for
9 papers
Multi-stage Progressive Compression of Conformer Transducer for On-device Speech Recognition
Jash Rathod, Nauman Dawalatabad, Shatrughan Singh +1
The smaller memory bandwidth in smart devices prompts development of smaller Automatic Speech Recognition (ASR) models. To obtain a smaller model, one can employ the model compress…
Two-Pass End-to-End ASR Model Compression
Nauman Dawalatabad, Tushar Vatsal, Ashutosh Gupta +4
Speech recognition on smart devices is challenging owing to the small memory footprint. Hence small size ASR models are desirable. With the use of popular transducer-based models,…
Formant Tracking Using Quasi-Closed Phase Forward-Backward Linear Prediction Analysis and Deep Neural Networks
Dhananjaya Gowda, Bajibabu Bollepalli, Sudarsana Reddy Kadiri +1
Formant tracking is investigated in this study by using trackers based on dynamic programming (DP) and deep neural nets (DNNs). Using the DP approach, six formant estimation method…
Streaming end-to-end speech recognition with jointly trained neural feature enhancement
Chanwoo Kim, Abhinav Garg, Dhananjaya Gowda +2
In this paper, we present a streaming end-to-end speech recognition model based on Monotonic Chunkwise Attention (MoCha) jointly trained with enhancement layers. Even though the Mo…
A review of on-device fully neural end-to-end automatic speech recognition algorithms
Chanwoo Kim, Dhananjaya Gowda, Dongsoo Lee +5
In this paper, we review various end-to-end automatic speech recognition algorithms and their optimization techniques for on-device applications. Conventional speech recognition sy…
Attention based on-device streaming speech recognition with large speech corpus
Kwangyoun Kim, Kyungmin Lee, Dhananjaya Gowda +10
In this paper, we present a new on-device automatic speech recognition (ASR) system based on monotonic chunk-wise attention (MoChA) models trained with large (> 10K hours) corpus.…