Papers › A neural attention model for speech command recognition

A neural attention model for speech command recognition

27 Aug 2018arXiv:1808.08929archive 2025-07-28

Douglas Coimbra de Andrade, Sabato Leo, Martin Loesener Da Silva Viana, Christoph Bernkopf

This paper introduces a convolutional recurrent network with attention for speech command recognition. Attention models are powerful tools to improve performance on natural language, image captioning and speech tasks. The proposed model establishes a new state-of-the-art accuracy of 94.1% on Google Speech Commands dataset V1 and 94.5% on V2 (for the 20-commands recognition task), while still keeping a small footprint of only 202K trainable parameters. Results are compared with previous convolutional implementations on 5 different tasks (20 commands recognition (V1 and V2), 12 commands recognition (V1), 35 word recognition (V1) and left-right (V1)). We show detailed performance results and demonstrate that the proposed attention mechanism not only improves performance but also allows inspecting what regions of the audio were taken into consideration by the network when outputting a given category.

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douglas125/SpeechCmdRecognition officialmentioned on GitHubtf report
Arizona-Voice/blossom mentioned on GitHubpytorch report
httttttt/ResNetAtentionBiLSTM mentioned on GitHubnot reachable when probed 2026-09-18 — repositories for recent papers often appear after camera-ready report
huckiyang/QuantumSpeech-QCNN mentioned on GitHubtf report
huckiyang/speech_quantum_dl mentioned on GitHubtf report
renyuanL/ry-Speech-commands mentioned on GitHubtf report
widzemin/audio_project mentioned on GitHubtf report

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1ran · honoured contract
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predict_audio douglas125/SpeechCmdRecognition/recognize_word.py official repository ran · our draft was wrong MIT (permissive) · 57c9801112b59c24 · report
normalize renyuanL/ry-Speech-commands/ryRecog03.py community (archive-listed) ran · honoured contract fingerprinted GPL-3.0 (copyleft) · pointer only · 720014c5cc086010 · report
ryGet1secSpeech renyuanL/ry-Speech-commands/ryRealTimeAsr03.py community (archive-listed) unverified GPL-3.0 (copyleft) · pointer only · 6fa05e75f626df54 · report

Tasks

Image Captioningmodel

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Keyword Spotting Google Speech Commands Attention RNN Google Speech Commands V1 12 95.6 #13 of 42 Archive leaderboard report
Keyword Spotting Google Speech Commands Attention RNN Google Speech Commands V1 2 99.2 #13 of 42 Archive leaderboard report
Keyword Spotting Google Speech Commands Attention RNN Google Speech Commands V1 20 94.1 #13 of 42 Archive leaderboard report
Keyword Spotting Google Speech Commands Attention RNN Google Speech Commands V1 35 94.3 #13 of 42 Archive leaderboard report
Keyword Spotting Google Speech Commands Attention RNN Google Speech Commands V2 12 96.9 #13 of 42 Archive leaderboard report
Keyword Spotting Google Speech Commands Attention RNN Google Speech Commands V2 2 99.4 #13 of 42 Archive leaderboard report
Keyword Spotting Google Speech Commands Attention RNN Google Speech Commands V2 20 94.5 #13 of 42 Archive leaderboard report
Keyword Spotting Google Speech Commands Attention RNN Google Speech Commands V2 35 93.9 #13 of 42 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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