Compute Cost Amortized Transformer for Streaming ASR Article Swipe
Yi Xie
,
Jonathan J. Macoskey
,
Martin Radfar
,
Feng-Ju Chang
,
Brian King
,
Ariya Rastrow
,
Athanasios Mouchtaris
,
Grant P. Strimel
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2207.02393
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2207.02393
We present a streaming, Transformer-based end-to-end automatic speech recognition (ASR) architecture which achieves efficient neural inference through compute cost amortization. Our architecture creates sparse computation pathways dynamically at inference time, resulting in selective use of compute resources throughout decoding, enabling significant reductions in compute with minimal impact on accuracy. The fully differentiable architecture is trained end-to-end with an accompanying lightweight arbitrator mechanism operating at the frame-level to make dynamic decisions on each input while a tunable loss function is used to regularize the overall level of compute against predictive performance. We report empirical results from experiments using the compute amortized Transformer-Transducer (T-T) model conducted on LibriSpeech data. Our best model can achieve a 60% compute cost reduction with only a 3% relative word error rate (WER) increase.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2207.02393
- https://arxiv.org/pdf/2207.02393
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4311914373
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4311914373Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2207.02393Digital Object Identifier
- Title
-
Compute Cost Amortized Transformer for Streaming ASRWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-07-05Full publication date if available
- Authors
-
Yi Xie, Jonathan J. Macoskey, Martin Radfar, Feng-Ju Chang, Brian King, Ariya Rastrow, Athanasios Mouchtaris, Grant P. StrimelList of authors in order
- Landing page
-
https://arxiv.org/abs/2207.02393Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2207.02393Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2207.02393Direct OA link when available
- Concepts
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Computer science, Inference, Computation, Transformer, Differentiable function, Decoding methods, Encoder, Architecture, Algorithm, Artificial intelligence, Mathematics, Operating system, Art, Voltage, Physics, Quantum mechanics, Visual arts, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.selective | 32 |
| abstract_inverted_index.arbitrator | 60 |
| abstract_inverted_index.end-to-end | 5, 55 |
| abstract_inverted_index.predictive | 88 |
| abstract_inverted_index.reductions | 41 |
| abstract_inverted_index.regularize | 81 |
| abstract_inverted_index.streaming, | 3 |
| abstract_inverted_index.throughout | 37 |
| abstract_inverted_index.LibriSpeech | 105 |
| abstract_inverted_index.computation | 24 |
| abstract_inverted_index.dynamically | 26 |
| abstract_inverted_index.experiments | 95 |
| abstract_inverted_index.frame-level | 65 |
| abstract_inverted_index.lightweight | 59 |
| abstract_inverted_index.recognition | 8 |
| abstract_inverted_index.significant | 40 |
| abstract_inverted_index.accompanying | 58 |
| abstract_inverted_index.architecture | 10, 21, 52 |
| abstract_inverted_index.performance. | 89 |
| abstract_inverted_index.amortization. | 19 |
| abstract_inverted_index.differentiable | 51 |
| abstract_inverted_index.Transformer-based | 4 |
| abstract_inverted_index.Transformer-Transducer | 100 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.6700000166893005 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile |