AUTOMATIC SPEECH RECOGNITION BASED UPON INFORMATION RETRIEVAL METHODS

• US 20110224982A1
• Filed: 03/12/2010
• Published: 09/15/2011
• Est. Priority Date: 03/12/2010
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Xiao, Xiaoqiang, Zweig, Geoffrey G., Acero, Alejandro, Droppo, James Garnet III
• Application Number:
  US12/722,556
• Publication Number:
  US 20110224982A1
• Time in Patent Office: Days
• US Class Current: 704/236
• CPC Class Codes: G10L 15/08 Speech classification or search
• CPC Class Codes: G10L 2015/025 Phonemes, fenemes or fenones being the recognition units

Abstract

Described is a technology in which information retrieval (IR) techniques are used in a speech recognition (ASR) system. Acoustic units (e.g., phones, syllables, multi-phone units, words and/or phrases) are decoded, and features found from those acoustic units. The features are then used with IR techniques (e.g., TF-IDF based retrieval) to obtain a target output (a word or words). Also described is the use of IR techniques to provide a full large vocabulary continuous speech (LVCSR) recognizer

Claims

1. In a computing environment, a system comprising:

a recognition mechanism that processes audio input into acoustic units;

a feature extraction mechanism that processes the acoustic units into features derived from the acoustic units; and

an information retrieval-based scoring mechanism that inputs the features and determines one or more words or acoustic scores associated with words based upon the features.

2. The system of claim 1 wherein the recognition mechanism outputs information corresponding to sub-word units, comprising phonemes, multi-phones or syllables, as the acoustic units.

3. The system of claim 1 wherein the recognition mechanism outputs information corresponding to words as the acoustic units.

4. The system of claim 1 wherein the features comprise one or more n-gram unit features.

5. The system of claim 1 wherein features comprise length-related information.

6. The system of claim 1 wherein the one or more words or acoustic scores are used by a telephony application.

7. The system of claim 1 wherein the one or more words or acoustic scores are used by a continuous speech recognizer, including by combining information retrieval-based acoustic scores associated with each word with a language model score to decode an utterance.

8. The system of claim 7 wherein the acoustic score is variable depending on whether there is an exact match between acoustic units and units in a dictionary used by the continuous speech recognizer.

9. The system of claim 1 wherein the one or more words or acoustic scores are used by a continuous speech recognizer, including by combining information retrieval-based acoustic scores associated with each word with length data and a language model score to decode an utterance.

10. The system of claim 1 wherein the information retrieval-based scoring mechanism comprises a vector space model-based scoring mechanism.

11. The system of claim 10 wherein the vector space model-based scoring mechanism is trained based upon TF-IDF counts in training data to determine term weights.

12. The system of claim 10 wherein the vector space model-based scoring mechanism is trained based upon training data and discriminative training to determine term weights.

13. The system of claim 1 wherein the information retrieval-based scoring mechanism comprises a language model-based scoring mechanism.

14. In a computing environment, a method performed on at least one processor, comprising, processing audio input into acoustic units, extracting features corresponding to the acoustic units, and using information retrieval-based scoring to determine acoustic scores for words based upon the features.

15. The method of claim 14 further comprising, providing a business listing based upon the acoustic scores for the words.

16. The method of claim 14 further comprising, using the acoustic scores for a plurality of candidate words with length data and a language model score to decode an utterance.

17. The method of claim 16 further comprising, determining whether there is an exact match between acoustic units and units in a dictionary, and if so, changing the acoustic score.

18. One or more computer-readable media having computer-executable instructions, which when executed perform steps, comprising:

receiving speech;

extracting units based upon the speech and hypothesized word boundaries;

determining candidate words that are associated with the units;

computing an information-retrieval based acoustic score for each candidate word and associating that acoustic score with that candidate word; and

sorting the candidate words by acoustic score.

19. The one or more computer-readable media of claim 18 having further computer-executable instructions comprising, combining at least some of the candidate words into n-gram sequences, and determining an utterance based on the scores associated with candidate words of an n-gram sequence with a language model score.

20. The one or more computer-readable media of claim 18 having further computer-executable instructions comprising, determining whether there is an exact match between a set of acoustic units corresponding to a word and units in a dictionary, and if so, changing the acoustic score associated with that word.