151 citations · 251 across the 10 of their papers we have counts for
4 papers · 1 filter
Fixed-point quantization aware training for on-device keyword-spotting
Sashank Macha, Om Oza, Alex Escott +5
Fixed-point (FXP) inference has proven suitable for embedded devices with limited computational resources, and yet model training is continually performed in floating-point (FLP).…
DeCoAR 2.0: Deep Contextualized Acoustic Representations with Vector Quantization
Shaoshi Ling, Yuzong Liu
Recent success in speech representation learning enables a new way to leverage unlabeled data to train speech recognition model. In speech representation learning, a large amount o…
Streaming Language Identification using Combination of Acoustic Representations and ASR Hypotheses
Chander Chandak, Zeynab Raeesy, Ariya Rastrow +5
This paper presents our modeling and architecture approaches for building a highly accurate low-latency language identification system to support multilingual spoken queries for vo…
Deep Contextualized Acoustic Representations For Semi-Supervised Speech Recognition
Shaoshi Ling, Yuzong Liu, Julian Salazar +1
We propose a novel approach to semi-supervised automatic speech recognition (ASR). We first exploit a large amount of unlabeled audio data via representation learning, where we rec…