Patent application EP20155262A (EP), filed 2020-02-04
Publication number: EP3699777A2
Title: A SYSTEM AND A METHOD FOR SPEECH ANALYSIS
Abstract: [0001]    Provided is a computer implemented method and system for processing an audio signal. The method comprises the steps of extracting prosodic features from the audio signal, aligning the extracted prosodic features with a script derived from or associated with the audio signal, and segmenting the script with said aligned extracted prosodic features into structural blocks of a first type. The method may include determining a distance measure between a structural block of a first type derived from the script with another structural block of the first type using, for example, the Damerau-Levenshtein distance.
IPC codes: G06F  16/    34            A I
G06F  16/   683            A I
G06F  40/   289            A I
G10L  25/    03            A I
G06F  16/    61            A I
G06F  16/   783            A I
G06F  16/   903            A I
Claims: number: 1
text: A computer implemented method of processing an audio signal, comprising the steps of:
number: 2
text: The method of claim 1, wherein the audio signal comprises digital audio clip of a human speech or a digital audio clip of a computer synthesized speech generated from a text.
number: 3
text: The method of claim 1, wherein the segmenting step simultaneously segments the script and the aligned extracted prosodic features into structural blocks of a first type, wherein the segmented structural blocks of a first type of the script comprise any one or any combination of clauses, phrases or sentences comprising the script.
number: 4
text: The method of claim 1, wherein the prosodic features are extracted from the audio signal to form a time series with a predefined, selected or calculated sample rate.
number: 5
text: The method of claim 4, wherein, after aligning the extracted prosodic features with a script derived from or associated with the audio signal, each structural block of a second type comprising the script is labelled with one or both of a start timestamp and an end timestamp, wherein the structural blocks of a second type comprising the script comprise any one or any combination of unigrams, bigrams and trigrams.
number: 6
text: The method of claim 1, further comprising the step of:
determining a distance measure between a structural block of the first type derived from the script with another structural block of the first type; wherein the distance measure comprises a measure of similarity between the structural block of the first type derived from the script and the other structural block of the first type.
number: 7
text: The method of claim 6, further comprising the steps of:
number: 8
text: The method of claim 7, wherein the edit distance between the POS for the structural block of the first type derived from the script and the POS for the other structural block of the first type is calculated using the Damerau-Levenshtein distance.
number: 9
text: The method of claim 6, wherein the measure of similarity between the structural block of the first type derived from the script and the other structural block of the first type is determined from the equation: CSS S 1 S 2 = min ∑ ‖ edits CS S 1 CS S 2 ‖
number: 10
text: A system for processing an audio signal, the system comprising:
number: 11
text: A computer implemented method of searching a speech dataset, the method comprising the steps of:
number: 12
text: The method of claim 12, wherein the step of identifying one or more other structural blocks of the first type in the speech dataset which have a same or similar POS as the inputted structural block of the first type identifies their associated scripts or speeches; and the one or more of the identified associated scripts or speeches are made available to a speech replay or speech synthesis module or system to audio play all of part of said associated scripts or speeches to a user.
number: 13
text: The method of claim 11, wherein the step of comparing said extracted POS sequence for said inputted structural block of the first type with POS sequences for structural blocks of the first type comprises determining a distance measure between the inputted structural block of a first type and each of the one or more other structural blocks of the first type in the speech dataset; with the distance measure comprising a measure of similarity between the inputted structural block of the first type and each of the one or more other structural blocks of the first type in the speech dataset.
number: 14
text: The method of claim 11, further comprising the step of calculating an edit distance between the POS for the inputted structural block of the first type and each of the one or more other structural blocks of the first type in the speech dataset; wherein the edit distance between the POS for the inputted structural block of the first type and each of the one or more other structural blocks of the first type in the speech dataset is calculated using the Damerau-Levenshtein distance.
number: 15
text: The method of claim 12, wherein the measure of similarity between the inputted structural block of the first type and each of the one or more other structural blocks of the first type in the speech dataset is determined from the equation: CSS S 1 S 2 = min ∑ ‖ edits CS S 1 CS S 2 ‖
Office action: search_report, dated 2020-08-26
Rejection reasons: novelty_epc_54
inventive_step_epc_56
Prior art cited: ref_id: - C. MANNINGM. SURDEANUJ. BAUERJ. FINKELS. BETHARDD. MCCLOSKY: "the stanford corenlp natural language processing tool", PROCEEDINGS OF THE 2014 ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: SYSTEM DEMONSTRATIONS, 2014, pages 55 - 60
ref_type: npl
severity: background
ref_id: - K. TOUTANOVAD. KLEINC. D. MANNINGY. SINGER: "Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology", vol. 1, 2003, ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, article "Feature-rich part-of-speech tagging with a cyclic dependency network", pages: 173 - 180
ref_type: npl
severity: background
ref_id: - E. BRILLR. C. MOORE: "In Proceedings of the 2000 Annual Meeting on Association for Computational Linguistics", 2000, ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, article "An improved error model for noisy channel spelling correction", pages: 286 - 293
ref_type: npl
severity: background
ref_id: US6636238
ref_type: patent
severity: background
ref_id: US2005216443
ref_type: patent
severity: novelty_destroying
ref_id: US2008077583
ref_type: patent
severity: obviousness
ref_id: EP2079234
ref_type: patent
severity: background
ref_id: US2013185057
ref_type: patent
severity: background
ref_id: US2018285326
ref_type: patent
severity: background
ref_id: US2018315428
ref_type: patent
severity: background
ref_id: - Andrey Kutuzov, "Improving English-Russian sentence alignment through POS tagging and Damerau-Levenshtein distance", Proceedings of the 4th Biennial International Workshop on Balto-Slavic Natural Language Processing, (20130808), pages 63 - 68, URL: https://www.aclweb.org/anthology/W13-2410.pdf, (20201118), XP055751909 [Y] 7-9,13-15 * abstract * * paragraph  [0002] *
ref_type: npl
severity: obviousness
Final disposition: pending (2020-08-26)