Dual-band speech encoding and estimating a narrowband speech feature from a wideband speech feature

• US 9,786,284 B2
• Filed: 08/14/2014
• Issued: 10/10/2017
• Est. Priority Date: 12/23/2010
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Acero, Alejandro, Droppo, III, James G., Seltzer, Michael L.
• Primary Examiner(s): Opsasnick, Michael N
• Application Number:
  US14/459,973
• Publication Number:
  US 20140358525A1
• Time in Patent Office: 1,153 Days
• Field of Search: 704205
• CPC Class Codes: G10L 15/02 Feature extraction for speech recognition; Selection of recognition unit
• CPC Class Codes: G10L 19/005 Correction of errors induced by the transmission channel, if related to the coding algorithm
• CPC Class Codes: G10L 19/20 using sound class specific coding, hybrid encoders or object based coding
• CPC Class Codes: G10L 2019/0001 Codebooks
• CPC Class Codes: G10L 21/038 using band spreading techniques

Abstract

This document describes various techniques for dual-band speech encoding. In some embodiments, a first type of speech feature is received from a remote entity, an estimate of a second type of speech feature is determined based on the first type of speech feature, the estimate of the second type of speech feature is provided to a speech recognizer, speech-recognition results based on the estimate of the second type of speech feature are received from the speech recognizer, and the speech-recognition results are transmitted to the remote entity.

Claims

1. A computing device comprising:

one or more computer processors;

one or more computer-readable media having instructions stored thereon that, responsive to execution by the one or more computer processors, perform operations comprising;

determining, based on one speech waveform, a wideband speech feature and a narrowband speech feature;

determining, based on the wideband speech feature, an estimate of the narrowband speech feature;

determining, based on the narrowband speech feature and the estimate of the narrowband speech feature, an estimation error of the estimate of the narrowband speech feature;

transmitting the wideband speech feature and the estimation error to a remote entity;

receiving, from the remote entity, data associated with a speech-based service based on the wideband speech feature; and

outputting, by the computing device, speech recognition results for the one speech waveform based on the received data associated with the speech-based service.

2. A computing device as described in claim 1, wherein the operations further comprise determining if sufficient bandwidth is available to transmit the estimation error of the narrowband speech feature and, when the sufficient bandwidth is available, transmitting the estimation error of the narrowband speech feature estimate.

3. A computing device as described in claim 1, wherein the operations further comprise encoding the wideband speech feature or the estimation error of the narrowband speech feature estimate using codebook-free encoding.

4. A computing device as described in claim 1, wherein the operations further comprise determining the narrowband speech feature estimate uses an affine transform.

5. A computing device as described in claim 1, wherein the operations further comprise encoding the wideband speech feature or the estimation error of the narrowband speech feature estimate using adaptive differential pulse-code modulation.

6. A computing device as described in claim 1, wherein the operations further comprise encoding the wideband speech feature with dynamic mean normalization.

7. A computing device as described in claim 1, wherein the operations further comprise determining the wideband speech feature and the narrowband speech feature comprises breaking the one speech waveform into a plurality of overlapping speech frames and extracting the wideband speech feature and the narrowband speech feature from the plurality of overlapping speech frames.

8. A computing device as described in claim 1, wherein the operations further comprise determining a floating point number representing the estimation error of the narrowband speech feature and transmitting the estimation error to the remote entity comprises transmitting the floating point number representing the estimation error of the narrowband speech feature.

9. A computing device as described in claim 1, wherein the speech recognition results comprise text, coordinates, a picture, an audio file, or a video file for output or display on the computing device.

10. A computing device as described in claim 1, wherein the speech recognition results are further processed by search, navigation, translation, or social networking services prior to being received by the computing device.

11. A computing device as described in claim 1, wherein the operations further comprise receiving the one speech waveform by the computing device via one or more microphones included in an audio interface of the computing device.

12. A computing device as described in claim 11, wherein the one or more microphones each have a bandwidth of at least 7 kHz.

13. A computing device comprising:

one or more computer processors;

one or more computer-readable media having instructions stored thereon that, responsive to execution by the one or more computer processors, perform operations comprising;

receiving, via a network interface of the computing device, a wideband speech feature from a remote entity;

determining an estimate of a narrowband speech feature based on the wideband speech feature;

providing the estimate of the narrowband speech feature to a speech recognizer trained on the narrowband speech features;

receiving, from the speech recognizer, speech-recognition results based on the estimate of the narrowband speech feature;

assembling the speech recognition results received from the speech recognizer; and

transmitting, via the network interface to the remote entity and for output or display by the remote entity, the assembled speech-recognition results based on the estimate of the narrowband speech feature.

14. A computing device as described in claim 13, wherein the operations further comprise providing the speech-recognition results of the speech recognizer trained on narrowband speech features to a search engine, receiving search results from the search engine, and transmitting the search results to the remote entity.

15. A computing device as described in claim 13, wherein the operations further comprise storing the wideband speech feature for training a second speech recognizer based on wideband speech features.

16. A computing device as described in claim 13, wherein determining the estimate of the narrowband speech feature uses an affine transform.

17. A computing device as described in claim 16, wherein parameters of the affine transform are based on a parallel set of the wideband speech features and the narrowband speech features.

18. One or non-transitory computer-readable storage memories storing instructions that upon execution by a computing device, cause the computing device to perform operations comprising:

receiving, from a remote entity, a wideband speech feature and an estimation error of a narrowband speech feature;

determining an estimate of a narrowband speech feature based on the wideband speech feature and the estimation error of the narrowband speech feature;

providing the estimate of the narrowband speech feature to a speech recognizer trained on narrowband speech features;

receiving, from the speech recognizer trained on narrowband speech features, speech-recognition results based on the estimate of the narrowband speech feature;

assembling the speech recognition results received from the speech recognizer; and

transmitting, to the remote entity and for output or display by the remote entity, the assembled speech-recognition results based on the estimate of the narrowband speech feature.

19. One or more non-transitory computer-readable storage memories as described in claim 18, wherein determining the estimate of the narrowband speech feature uses a pseudo-inverse derivation model.

20. One or more non-transitory computer-readable storage memories as described in claim 18, wherein the operations further comprise storing the wideband speech feature for training a second speech recognizer based on the wideband speech feature.