2215 results about "Speech identification" patented technology

A self-contained wireless interactive speech recognition control device and system that integrates with automated systems and appliances to provide totally hands-free speech control capabilities for a given space. Preferably, each device comprises a programmable microcontroller having embedded speech recognition and audio output capabilities, a microphone, a speaker and a wireless communication system through which a plurality of devices can communicate with each other and with one or more system controllers or automated mechanisms. The device may be enclosed in a stand-alone housing or within a standard electrical wall box. Several devices may be installed in close proximity to one another to ensure hands-free coverage throughout the space. When two or more devices are triggered simultaneously by the same speech command, real time coordination ensures that only one device will respond to the command.

A voice-enabled help desk service is disclosed. The service comprises an automatic speech recognition module for recognizing speech from a user, a spoken language understanding module for understanding the output from the automatic speech recognition module, a dialog management module for generating a response to speech from the user, a natural voices text-to-speech synthesis module for synthesizing speech to generate the response to the user, and a frequently asked questions module. The frequently asked questions module handles frequently asked questions from the user by changing voices and providing predetermined prompts to answer the frequently asked question.

A computer is used to perform recorded actions. The computer receives recorded spoken utterances of actions. The computer then performs speech recognition on the recorded spoken utterances to generate texts of the actions. The computer then parses the texts to determine properties of the actions. After parsing the texts, permits the user to indicate that the user has reviewed one or more actions. The computer then automatically carries out the actions indicated as having been reviewed by the user.

A system and method for a highly interactive style of speech-to-speech translation is provided. The interactive procedures enable a user to recognize, and if necessary correct, errors in both speech recognition and translation, thus providing robust translation output than would otherwise be possible. The interactive techniques for monitoring and correcting word ambiguity errors during automatic translation, search, or other natural language processing tasks depend upon the correlation of Meaning Cues and their alignment with, or mapping into, the word senses of third party lexical resources, such as those of a machine translation or search lexicon. This correlation and mapping can be carried out through the creation and use of a database of Meaning Cues, i.e., SELECT. Embodiments described above permit the intelligent building and application of this database, which can be viewed as an interlingua, or language-neutral set of meaning symbols, applicable for many purposes. Innovative techniques for interactive correction of server-based speech recognition are also described.

A system and method for processing speech input comprising a speech recognizer and a logical command processor which facilitates additional processing of speech input beyond the speech recognizer level. A speech recognizer receives input from a user, and when a command is identified in the speech input, if the command meets conditions that require additional processing, a representation of the speech input s stored for subsequent processing. A logical command processor performs additional processing of command input by analyzing the command and its elements, determining which elements are required for successful processing the command and which elements are present and lacking. The user is prompted to supply missing information, and subsequent user input is added to the command structure until the command input is aborted or the command structure reaches sufficient completeness to enable execution of the command. Thereby, speech input of complex commands in natural language in a system running a plurality of applications and processes is made possible.

A speech translation system and methods for cross-lingual communication that enable users to improve and modify content and usage of the system and easily abort or reset translation. The system includes a speech recognition module configured for accepting an utterance, a machine translation module, an interface configured to communicate the utterance and proposed translation, a correction module and an abort action unit that removes any hypotheses or partial hypotheses and terminates translation. The system also includes modules for storing favorites, changing language mode, automatically identifying language, providing language drills, viewing third party information relevant to conversation, among other things.

A system and method provides universal access to voice-based documents containing information formatted using MIME and HTML standards using customized extensions for voice information access and navigation. These voice documents are linked using HTML hyper-links that are accessible to subscribers using voice commands, touch-tone inputs and other selection means. These voice documents and components in them are addressable using HTML anchors embedding HTML universal resource locators (URLs) rendering them universally accessible over the Internet. This collection of connected documents forms a voice web. The voice web includes subscriber-specific documents including speech training files for speaker dependent speech recognition, voice print files for authenticating the identity of a user and personal preference and attribute files for customizing other aspects of the system in accordance with a specific subscriber.

The error rate of a pronunciation guesser that guesses the phonetic spelling of words used in speech recognition is improved by causing its training to weigh letter-to-phoneme mappings used as data in such training as a function of the frequency of the words in which such mappings occur. Preferably the ratio of the weight to word frequency increases as word frequencies decreases. Acoustic phoneme models for use in speech recognition with phonetic spellings generated by a pronunciation guesser that makes errors are trained against word models whose phonetic spellings have been generated by a pronunciation guesser that makes similar errors. As a result, the acoustic models represent blends of phoneme sounds that reflect the spelling errors made by the pronunciation guessers. Speech recognition enabled systems are made by storing in them both a pronunciation guesser and a corresponding set of such blended acoustic models.

A speech dialog system wherein a process for automatic control of devices by speech dialog is used applying methods of speech input, speech signal processing and speech recognition, syntatical-grammatical postediting as well as dialog, executive sequencing and interface control, and which is characterized in that syntax and command structures are set during real-time dialog operation; preprocessing, recognition and dialog control are designed for operation in a noise-encumbered environment; no user training is required for recognition of general commands; training of individual users is necessary for recognition of special commands; the input of commands is done in linked form, the number of words used to form a command for speech input being variable; a real-time processing and execution of the speech dialog is established; and the speech input and output is done in the hands-free mode.

The disclosure describes an overall system/method for text-input using a multimodal interface with speech recognition. Specifically, pluralities of modes interact with the main speech mode to provide the speech-recognition system with partial knowledge of the text corresponding to the spoken utterance forming the input to the speech recognition system. The knowledge from other modes is used to dynamically change the ASR system's active vocabulary thereby significantly increasing recognition accuracy and significantly reducing processing requirements. Additionally, the speech recognition system is configured using three different system configurations (always listening, partially listening, and push-to-speak) and for each one of those three different user-interfaces are proposed (speak-and-type, type-and-speak, and speak-while-typing). Finally, the overall user-interface of the proposed system is designed such that it enhances existing standard text-input methods; thereby minimizing the behavior change for mobile users.

A system for substantially automating transcription services for multiple voice users including a manual transcription station, a speech recognition program and a routing program. The system establishes a profile for each of the voice users containing a training status which is selected from the group of enrollment, training, automated and stop automation. When the system receives a voice dictation file from a current voice user based on the training status the system routes the voice dictation file to a manual transcription station and the speech recognition program. A human transcriptionist creates transcribed files for each received voice dictation files. The speech recognition program automatically creates a written text for each received voice dictation file if the training status of the current user is training or automated. A verbatim file is manually established if the training status of the current user is enrollment or training and the speech recognition program is trained with an acoustic model for the current user using the verbatim file and the voice dictation file if the training status of the current user is enrollment or training. The transcribed file is returned to the current user if the training status of the current user is enrollment or training or the written text is returned if the training status of the current user is automated. An apparatus and method is also disclosed for simplifying the manual establishment of the verbatim file. A method for substantially automating transcription services is also disclosed.

A speech control system that can recognize a spoken command and associated words (such as “call mom at home”) and can cause a selected application (such as a telephone dialer) to execute the command to cause a data processing system, such as a smartphone, to perform an operation based on the command (such as look up mom's phone number at home and dial it to establish a telephone call). The speech control system can use a set of interpreters to repair recognized text from a speech recognition system, and results from the set can be merged into a final repaired transcription which is provided to the selected application.

A speech recognition system recognizes an input speech signal by using a first speech recognizer and a second speech recognizer each coupled to a decision module. Each of the first and second speech recognizers outputs first and second recognized speech texts and first and second associated confidence scores, respectively, and the decision module selects either the first or the second speech text depending upon which of the first or second confidence score is higher. The decision module may also adjust the first and second confidence scores to generate first and second adjusted confidence scores, respectively, and select either the first or second speech text depending upon which of the first or second adjusted confidence scores is higher. The first and second confidence scores may be adjusted based upon the location of a speaker, the identity or accent of the speaker, the context of the speech, and the like.

The invention relates to a method and apparatus for training a multilingual speech model set. The multilingual speech model set generated is suitable for use by a speech recognition system for recognizing spoken utterances for at least two different languages. The invention allows using a single speech recognition unit with a single speech model set to perform speech recognition on utterances from two or more languages. The method and apparatus make use of a group of a group of acoustic sub-word units comprised of a first subgroup of acoustic sub-word units associated to a first language and a second subgroup of acoustic sub-word units associated to a second language where the first subgroup and the second subgroup share at least one common acoustic sub-word unit. The method and apparatus also make use of a plurality of letter to acoustic sub-word unit rules sets, each letter to acoustic sub-word unit rules set being associated to a different language. A set of untrained speech models is trained on the basis of a training set comprising speech tokens and their associated labels in combination with the group of acoustic sub-word units and the plurality of letter to acoustic sub-word unit rules sets. The invention also provides a computer readable storage medium comprising a program element for implementing the method for training a multilingual speech model set.

A computer implemented method for automatically processing a data request comprising accessing a voice signal from a caller, determining geographic information associated with the caller from telephone network information associated with a call made by the caller, and retrieving a speech recognition grammar customized to the geographic information associated with the caller. The method further includes recognizing the voice signal by matching the voice signal to an entry of the speech recognition grammar and providing a directory listing to the caller based on the entry of the speech recognition grammar. The selected grammar may be customized to bias speech recognition to more frequently recognize cities local to the geographic information.

An adaptive speech recognition system is provided including an input for receiving a signal derived from a spoken utterance indicative of a certain vocabulary item, a speech recognition dictionary, a speech recognition unit and an adaptation module. The speech recognition dictionary has a plurality of vocabulary items each being associated to a respective dictionary transcription group. The speech recognition unit is in an operative relationship with the speech recognition dictionary and selects a certain vocabulary item from the speech recognition dictionary as being a likely match to the signal received at the input. The results of the speech recognition process are provided to the adaptation module. The adaptation module includes a transcriptions bank having a plurality of orthographic groups, each including a plurality of transcriptions associated with a common vocabulary item. A transcription selector module in the adaptation module retrieves a given orthographic group from the transcriptions bank on a basis of the vocabulary item recognized by the speech recognition unit. The transcription selector module processes the given orthographic group on the basis of the signal received at the input to select a certain transcription from the transcriptions bank. The adaptation module then modifies a dictionary transcription group corresponding to the vocabulary item selected as being a likely match to the signal received at the input on the basis of the selected certain transcription.

An automated “Voice Search Message Service” provides a voice-based user interface for generating text messages from an arbitrary speech input. Specifically, the Voice Search Message Service provides a voice-search information retrieval process that evaluates user speech inputs to select one or more probabilistic matches from a database of pre-defined or user-defined text messages. These probabilistic matches are also optionally sorted in terms of relevancy. A single text message from the probabilistic matches is then selected and automatically transmitted to one or more intended recipients. Optionally, one or more of the probabilistic matches are presented to the user for confirmation or selection prior to transmission. Correction or recovery of speech recognition errors avoided since the probabilistic matches are intended to paraphrase the user speech input rather than exactly reproduce that speech, though exact matches are possible. Consequently, potential distractions to the user are significantly reduced relative to conventional speech recognition techniques.

The disclosure describes an overall system/method for text-input using a multimodal interface with a combination of speech recognition and text prediction. Specifically, an “always listening” mode for entering words is combined with a push-to-speak mode for entering symbols and phrases. In addition, these two modes are further combined with keypad based text prediction. Finally, the overall user-interface of the proposed system is designed such that it enhances existing standard text-input methods; thereby minimizing the behavior change for mobile users.

Systems and methods providing for secure voice print authentication over a network are disclosed herein. During an enrollment stage, a client's voice is recorded and characteristics of the recording are used to create and store a voice print. When an enrolled client seeks access to secure information over a network, a sample voice recording is created. The sample voice recording is compared to at least one voice print. If a match is found, the client is authenticated and granted access to secure information.

Systems and methods providing for a dual use voice analysis system are disclosed herein. Speech recognition is achieved by comparing characteristics of words spoken by a speaker to one or more templates of human language words. Speaker identification is achieved by comparing characteristics of a speaker's speech to one or more templates, or voice prints. The system is adapted to increase or decrease matching constraints depending on whether speaker identification or speaker recognition is desired.

A method for speech recognition includes providing a source of geographical information within a vehicle. The geographical information pertains to a current location of the vehicle, a planned travel route of the vehicle, a map displayed within the vehicle, and/or a gesture marked by a user on a map. Words spoken within the vehicle are recognized by use of a speech recognition module. The recognizing is dependent upon the geographical information.

In embodiments of the present invention, a system and computer-implemented method for enabling dictation may include parsing standard reports in order to identify a plurality of logical phrases in the report used for discrete sections and descriptions. In the report method, the phrases may be parsed and identifier words throughout the report may be compared to eliminate ambiguities. The method may then involve constructing text macros that follow the parsed text, thereby enabling the user to speak the identifiers to indicate full, formatted text. Finally, the report method may involve constructing a mnemonic document so both beginner and experienced users can easily read the identifiers out loud to produce a report. The result of the method is an intuitive, notes-style way to use speech commands to quickly produce a standard, formatted report.

Pronunciation correction for text-to-speech (TTS) systems and speech recognition (SR) systems between different languages is provided. If a word requiring pronunciation by a target language TTS or SR is from a same language as the target language, but is not found in a lexicon of words from the target language, a letter-to-speech (LTS) rules set of the target language is used to generate a letter-to-speech output for the word for use by the TTS or SR configured according to the target language. If the word is from a different language as the target language, phonemes comprising the word according to its native language are mapped to phonemes of the target language. The phoneme mapping is used by the TTS or SR configured according to the target language for generating or recognizing an audible form of the word according to the target language.

An exception dictionary creating device, an exception dictionary creating method, and a program therefor allowing creating an exception dictionary are provided for affording high speech recognition performance while reducing the size of the exception dictionary, as well as a speech recognition device and a speech recognition method capable of recognizing a speech with high accuracy of recognition by using the exception dictionary. To achieve this, a text-to-phonetic symbol converting unit (21) of an exception dictionary creating device (10) creates converted phonetic symbol sequence by converting text sequence of vocabulary list data (21) into phonetic symbol sequence. A recognition degradation contribution degree calculating unit (24) calculates a recognition degradation contribution degree when the converted phonetic symbol sequence is not identical to a correct phonetic symbol sequence registered in a database or word dictionary (50). An exception dictionary registering unit (41) registers in the exception dictionary (60) the text sequence and the phonetic symbol sequence registered in the text sequence of the vocabulary list data (12) with a high degree of recognition degradation contribution degree to the recognition so as not to exceed data limitation capacity indicated by exception dictionary memory size content (71).

A wireless system comprises at least one subscriber unit in wireless communication with an infrastructure. Each subscriber unit implements a speech recognition client, and the infrastructure comprises a speech recognition server. A given subscriber unit takes as input an unencoded speech signal that is subsequently parameterized by the speech recognition client. The parameterized speech is then provided to the speech recognition server that, in turn, performs speech recognition analysis on the parameterized speech. Information signals, based in part upon any recognized utterances identified by the speech recognition analysis, are subsequently provided to the subscriber unit. The information signals may be used to control the subscriber unit itself; to control one or more devices coupled to the subscriber unit, or may be operated upon by the subscriber unit or devices coupled thereto.

Methods and systems are provided for receiving a communication, analyzing the communication in real-time or near real-time using a computer-based communications analytics facility for at least one of a language characteristic and an acoustic characteristic, wherein for analyzing the language characteristic of voice communications, the communication is converted to text using computer-based speech recognition, determining at least one of the category, the score, the sentiment, or the alert associated with the communication using the at least one language and/or acoustic characteristic, and providing a dynamic graphical representation of the at least one category, score, sentiment, or alert through a graphical user interface.

A system, method and computer program product for determining an address of an entity based on a user location are disclosed. An utterance representative of an entity is initially received from a user. The entity associated with the utterance is then recognized using a speech recognition process. Next, a location of the user is determined. A query is performed to identify a plurality of locations associated with the entity. Based on the results of the query and the location of the user, it is ascertained which of the identified locations associated with the entity are in proximity to the location of the user.

A system and method for rescoring the N-best hypotheses from an automatic speech recognition system by comparing an original speech waveform to synthetic speech waveforms that are generated for each text sequence of the N-best hypotheses. A distance is calculated from the original speech waveform to each of the synthesized waveforms, and the text associated with the synthesized waveform that is determined to be closest to the original waveform is selected as the final hypothesis. The original waveform and each synthesized waveform are aligned to a corresponding text sequence on a phoneme level. The mean of the feature vectors which align to each phoneme is computed for the original waveform as well as for each of the synthesized hypotheses. The distance of a synthesized hypothesis to the original speech signal is then computed as the sum over all phonemes in the hypothesis of the Euclidean distance between the means of the feature vectors of the frames aligning to that phoneme for the original and the synthesized signals. The text of the hypothesis which is closest under the above metric to the original waveform is chosen as the final system output.

A method, system, and computer program product for autonomously transcribing and building tagging data of a conversation. A corpus processing agent monitors a conversation and utilizes a speech recognition agent to identify the spoken languages, speakers, and emotional patterns of speakers of the conversation. While monitoring the conversation, the corpus processing agent determines emotional patterns by monitoring voice modulation of the speakers and evaluating the context of the conversation. When the conversation is complete, the corpus processing agent determines synonyms and paraphrases of spoken words and phrases of the conversation taking into consideration any localized dialect of the speakers. Additionally, metadata of the conversation is created and stored in a link database, for comparison with other processed conversations. A corpus, a transcription of the conversation containing metadata links, is then created. The corpus processing agent also determines the frequency of spoken keywords and phrases and compiles a popularity index.

A multi-stage speech recognition system includes an audio transducer that detects a speech signal, and a sampling circuit that converts the transducer output into a digital speech signal. A spectral analysis circuit identifies a portion of the speech signal corresponding to a first class and a second class. The system includes memory storage or a database having a first and a second vocabulary list. A recognition circuit recognizes the first class based on the first vocabulary list to obtain a first recognition result. A matching circuit restricts a vocabulary list based on the first recognition result, and a recognizing circuit recognizes the second class based on the restricted vocabulary list, to obtain a second recognition result.

A method, apparatus, and system are described for a continuous speech recognition engine that includes a fine speech recognizer model, a coarse sound representation generator, and a coarse match generator. The fine speech recognizer model receives a time coded sequence of sound feature frames, applies a speech recognition process to the sound feature frames and determines at least a best guess at each recognizable word that corresponds to the sound feature frames. The coarse sound representation generator generates a coarse sound representation of the recognized word. The coarse match generator determines a likelihood of the coarse sound representation actually being the recognized word based on comparing the coarse sound representation of the recognized word to a database containing the known sound of that recognized word and assigns the likelihood as a robust confidence level parameter to that recognized word.