1
Stephane H Maes, David M Lubensky, Andrzej Sakrajda: Universal IP-based and scalable architectures across conversational applications using web services for speech and audio processing resources. International Business Machines Corporation, F Chau & Associates, October 5, 2004: US06801604 (356 worldwide citation)

Systems and methods for conversational computing and, in particular, to systems and methods for building distributed conversational applications using a Web services-based model wherein speech engines (e.g., speech recognition) and audio I/O systems are programmable services that can be asynchronous ...


2
George J Vysotsky, Ayman O Asadi, David M Lubensky, Vijay R Raman, Jayant M Naik: Methods and apparatus for activating telephone services in response to speech. NYNEX Science & Technology, Michael P Straub, Peter L Michaelson, Michaelson & Wallace, February 17, 1998: US05719921 (170 worldwide citation)

Methods and apparatus for activating telephone services in response to speech are described. A directory including names is maintained for each customer. A speaker dependent speech template and a telephone number for each name, is maintained as part of each customer's directory. Speaker independent ...


3
George J Vysotsky, Ayman O Asadi, David M Lubensky, Vijay R Raman, Jayant M Naik: Methods and apparatus for performing speaker independent recognition of commands in parallel with speaker dependent recognition of names, words or phrases. Nynex Science & Technology, Peter L Michaelson, Michael P Straub, Michaelson & Wallace, November 3, 1998: US05832063 (96 worldwide citation)

Methods and apparatus for activating telephone services in response to speech are described. A directory including names is maintained for each customer. A speaker dependent speech template and a telephone number for each name, is maintained as part of each customer's directory. Speaker independent ...


4
Osamuyimen T Stewart, David M Lubensky: Using partial information to improve dialog in automatic speech recognition systems. International Business Machines Corporation, Scully Scott Murphy & Presser P C, Anne V Dougherty Esq, October 14, 2008: US07437291 (14 worldwide citation)

A method, system and computer readable device for recognizing a partial utterance in an automatic speech recognition (ASR) system where said method comprising the steps of, receiving, by a ASR recognition unit, an input signal representing a speech utterance or word and transcribing the input signal ...


5
David M Lubensky: Automated speech recognition using a plurality of different multilayer perception structures to model a plurality of distinct phoneme categories. NYNEX Science & Technology Corporation, Michael P Straub, Peter L Michaelson, Michaelson & Wallace, April 28, 1998: US05745649 (14 worldwide citation)

For speech recognition systems a method for modeling context-dependent phonetic categories using artificial neural nets has been described. First, linguistically motivated context-clustering is employed to reduce the number of context-dependent categories. Second, phone-specific MLP structures are u ...


6
Dongsuk Yuk, David M Lubensky: Unsupervised incremental adaptation using maximum likelihood spectral transformation. International Business Machines Corporation, Ryan Mason & Lewis, February 14, 2006: US06999926 (11 worldwide citation)

A maximum likelihood spectral transformation (MLST) technique is proposed for rapid speech recognition under mismatched training and testing conditions. Speech feature vectors of real-time utterances are transformed in a linear spectral domain such that a likelihood of the utterances is increased af ...


7
Osamuyimen T Stewart, David M Lubensky: Using partial information to improve dialog in automatic speech recognition systems. Nuance Communications, Wolf Greenfield & Sacks P C, November 24, 2009: US07624014 (8 worldwide citation)

A method, system and computer readable device for recognizing a partial utterance in an automatic speech recognition (ASR) system where said method comprising the steps of, receiving, by a ASR recognition unit, an input signal representing a speech utterance or word and transcribing the input signal ...


8
Raymond L Co, Ea Ee Jan, David M Lubensky: Method and system for improved speech recognition. Nuance Communications, Wolf Greenfield & Sacks P C, March 16, 2010: US07680661 (8 worldwide citation)

A method for speech recognition includes: prompting a user with a first query to input speech into a speech recognition engine; determining if the inputted speech is correctly recognized; wherein in the event the inputted speech is correctly recognized proceeding to a new task; wherein in the event ...


9
Dongsuk Yuk, David M Lubensky: Unsupervised incremental adaptation using maximum likelihood spectral transformation. International Business Machines Corporation, Anne V Dougherty, Ryan Mason & Lewis, September 11, 2007: US07269555 (7 worldwide citation)

In a speech recognition system, a method of transforming speech feature vectors associated with speech data provided to the speech recognition system includes the steps of receiving likelihood of utterance information corresponding to a previous feature vector transformation, estimating one or more ...


10
Andrew Aaron, Subrata K Das, David M Lubensky: Apparatus, program storage device and method for testing speech recognition in the mobile environment of a vehicle. International Business Machines Corporation, Ference & Associates, February 3, 2009: US07487084 (6 worldwide citation)

A testing arrangement provided for speech recognition systems in vehicles. Preferably included are a “mobile client” secured in the vehicle and driven around at a desired speed, an audio system and speaker which plays back a set of prerecorded utterances stored digitally in a computer arrangement su ...