Multi-task Learning for Voice Trigger Detection

01/26/2020
by   Siddharth Sigtia, et al.
0

We describe the design of a voice trigger detection system for smart speakers. In this study, we address two major challenges. The first is that the detectors are deployed in complex acoustic environments with external noise and loud playback by the device itself. Secondly, collecting training examples for a specific keyword or trigger phrase is challenging resulting in a scarcity of trigger phrase specific training data. We describe a two-stage cascaded architecture where a low-power detector is always running and listening for the trigger phrase. If a detection is made at this stage, the candidate audio segment is re-scored by larger, more complex models to verify that the segment contains the trigger phrase. In this study, we focus our attention on the architecture and design of these second-pass detectors. We start by training a general acoustic model that produces phonetic transcriptions given a large labelled training dataset. Next, we collect a much smaller dataset of examples that are challenging for the baseline system. We then use multi-task learning to train a model to simultaneously produce accurate phonetic transcriptions on the larger dataset and discriminate between true and easily confusable examples using the smaller dataset. Our results demonstrate that the proposed model reduces errors by half compared to the baseline in a range of challenging test conditions without requiring extra parameters.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/11/2020

Modeling Prosodic Phrasing with Multi-Task Learning in Tacotron-based TTS

Tacotron-based end-to-end speech synthesis has shown remarkable voice qu...
research
06/23/2022

Adversarial Multi-Task Learning for Disentangling Timbre and Pitch in Singing Voice Synthesis

Recently, deep learning-based generative models have been introduced to ...
research
10/29/2020

Progressive Voice Trigger Detection: Accuracy vs Latency

We present an architecture for voice trigger detection for virtual assis...
research
08/05/2020

Hybrid Transformer/CTC Networks for Hardware Efficient Voice Triggering

We consider the design of two-pass voice trigger detection systems. We f...
research
05/14/2021

Streaming Transformer for Hardware Efficient Voice Trigger Detection and False Trigger Mitigation

We present a unified and hardware efficient architecture for two stage v...
research
03/23/2023

A Deliberation-based Joint Acoustic and Text Decoder

We propose a new two-pass E2E speech recognition model that improves ASR...
research
12/07/2022

Tree DNN: A Deep Container Network

Multi-Task Learning (MTL) has shown its importance at user products for ...

Please sign up or login with your details

Forgot password? Click here to reset