Language models using spoken language modeling
US-2024386885-A1 · Nov 21, 2024 · US
US8990076B1 · US · B1
| Field | Value |
|---|---|
| Publication number | US-8990076-B1 |
| Application number | US-201213608340-A |
| Country | US |
| Kind code | B1 |
| Filing date | Sep 10, 2012 |
| Priority date | Sep 10, 2012 |
| Publication date | Mar 24, 2015 |
| Grant date | Mar 24, 2015 |
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In automated speech recognition (ASR), multiple devices may be employed to perform the ASR in a distributed environment. To reduce bandwidth use in transmitting between devices ASR information is compressed prior to transmission. To counteract fidelity loss that may accompany such compression, two versions of an audio signal are processed by an acoustic front end (AFE), one version is unaltered and one is compressed and decompressed prior to AFE processing. The two versions are compared, and the comparison data is sent to a recipient for further ASR processing. The recipient uses the comparison data and a received version of the compressed audio signal to recreate the post-AFE processing results from the received audio signal. The result is improved ASR results and decreased bandwidth usage between distributed ASR devices.
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What is claimed is: 1. A system for distributed processing of audio data for speech recognition, comprising: a client device configured to: receive a digital signal comprising data representing speech, compress the digital signal to create a compressed digital signal, decompress the compressed digital signal to create a decompressed digital signal, process the decompressed digital signal to create a first set of feature vectors, process the digital signal to create a seco…
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