A robust keyword detection system for criminal scene analysis

Zheng, Nengheng; Xia, Li

doi:10.1109/iciea.2010.5516656

Cited by 5 publications

(1 citation statement)

References 9 publications

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“…It can be applied off-line for fast search in recorded utterances (e.g. telephone calls analysed by police [1]), large spoken corpora (like broadcast archives [2]), or data collected by call-centres [3]. There are also on-line applications, namely for instant alerting, used in media monitoring [4] or in keyword activated mobile services [5].…”

Section: Introductionmentioning

confidence: 99%

Very Fast Keyword Spotting System with Real Time Factor below 0.01

Nouza,

Cerva,

Zdansky

2020

Preprint

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In the paper we present an architecture of a keyword spotting (KWS) system that is based on modern neural networks, yields good performance on various types of speech data and can run very fast. We focus mainly on the last aspect and propose optimizations for all the steps required in a KWS design: signal processing and likelihood computation, Viterbi decoding, spot candidate detection and confidence calculation. We present time and memory efficient modelling by bidirectional feedforward sequential memory networks (an alternative to recurrent nets) either by standard triphones or so called quasi-monophones, and an entirely forward decoding of speech frames (with minimal need for look back). Several variants of the proposed scheme are evaluated on 3 large Czech datasets (broadcast, internet and telephone, 17 hours in total) and their performance is compared by Detection Error Tradeoff (DET) diagrams and real-time (RT) factors. We demonstrate that the complete system can run in a single pass with a RT factor close to 0.001 if all optimizations (including a GPU for likelihood computation) are applied.

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Section: Introductionmentioning

confidence: 99%