Method for voicemail quality detection
AssigneeNuance Communications, Inc.
InventorsDushyant Sharma, Patrick Naylor
Life of this patent
Estimating the term…
Abstract
A system and method for speech quality detection is included. The method may include receiving, at a computing device, a first speech signal associated with a particular user. The method may include extracting one or more short-term features from the first speech signal wherein extracting short-term features includes extracting a time frame of between 10-50 ms. The method may also include determining one or more statistics of each of the one or more short-term features from the first speech signal. The method may further include classifying the one or more statistics as belonging to one of a set of quality classes.
Claims17
A computer-implemented method for non-intrusive speech quality detection without a reference signal comprising:
- receiving, at a computing device configured to convert voicemail to text, a first speech signal associated with a user;
- extracting one or more short-term features from the first speech signal wherein extracting short-term features includes extracting a time frame of between 10-50 ms, wherein the one or more short term features include a Hilbert envelope based feature and a linear predictive coding residual;
- determining one or more statistics of each of the one or more short-term features from the first speech signal;
- classifying the one or more statistics as belonging to one of a set of quality classes, wherein classifying the one or more statistics includes modeling a speech quality class using a binary tree classifier;
- and
- automatically generating at least one training database, based upon, at least in part, the first speech signal and an intrusive speech quality algorithm, wherein the intrusive speech quality algorithm is not used during the receiving, extracting, determining, and classifying operations.
A non-transitory computer-readable storage medium having stored thereon instructions, which when executed by a processor result in one or more operations for non-intrusive speech quality detection without a reference signal, the operations comprising:
- receiving, at a computing device configured to convert voicemail to text, a first speech signal associated with a particular user;
- extracting one or more short-term features from the first speech signal wherein extracting short-term features includes extracting a time frame of between 10-50 ms, wherein the one or more short term features include a Hilbert envelope based feature and a linear predictive coding residual;
- determining one or more statistics of each of the one or more short-term features from the first speech signal;
- classifying the one or more statistics as belonging to one of a set of quality classes, wherein classifying the one or more statistics includes modeling a speech quality class using a binary tree classifier;
- and
- automatically generating at least one training database, based upon, at least in part, the first speech signal and an intrusive speech quality algorithm, wherein the intrusive speech quality algorithm is not used during the receiving, extracting, determining, and classifying operations.
A voicemail to text system configured to perform non-intrusive speech quality detection without a reference signal comprising:
- one or more processors configured to receive a first speech signal associated with a particular user, the one or more processors further configured to extract one or more short-term features from the first speech signal wherein extracting short-term features includes extracting a time frame of between 10-50 ms, wherein the one or more short term features include a Hilbert envelope based feature and a linear predictive coding residual, the one or more processors further configured to determine one or more statistics of each of the one or more short-term features from the first speech signal, the one or more processors further configured to classify the one or more statistics as belonging to one of a set of quality classes, wherein classifying the one or more statistics includes modeling a speech quality class using a binary tree classifier, the one or more processors further configured to automatically generate at least one training database, based upon, at least in part, the first speech signal and an intrusive speech quality algorithm, wherein the intrusive speech quality algorithm is not used during the receiving, extracting, determining, and classifying operations.
Dependencies are inferred from the claim text.