Matthew D. Crane - Charlestown MA, US Mark Arthur Holthouse - Newtonville MA, US John Ngoc Nguyen - Arlington MA, US Michael Stuart Phillips - Belmont MA, US Stephen Richard Springer - Needham MA, US
International Classification:
G10L 21/00 G10L 15/20
US Classification:
704275, 704233
Abstract:
A speech recognition system plays prompts to a user in order to obtain information from the user. If the user begins to speak, the prompt should stop. However, the system may receive sounds other than speech from the user while playing a prompt, in which case the prompt should continue. The system temporarily stops a prompt when it detects a sound or when it preliminarily determines that a detected sound may be a target sound (such as words from the user). The system then determines whether the received sound is a target sound or some other sound (such as coughing or a door shutting). If the received sound is not determined to be a target sound, then the prompt is resumed. The prompt can be resumed at any appropriate point, such as the point where it was stopped, a prior phrase boundary, or the beginning of the prompt.
Minimal Distraction Capture Of Spoken Contact Information
Real-time automatic capturing and storing is described for contact information such as a telephone number or other well-structured contact information spoken during a conversation over the mobile telephone. A user input is received to capture contact information contained in recent audio data processed by the mobile device. Speech in the recent audio data is identified that corresponds to the contact information. Then speech recognition is used to extract the contact information from the identified speech. The contact information is stored in mobile device memory storage.
A call from a caller to an interactive voice response (IVR) system may be serviced based on behavior by the caller in one or more prior calls to the IVR system. The call may be serviced by predicting information to be used in servicing the call. Predicting such information may include analyzing data reflecting behavior by the caller in one or more prior calls to the IVR system.
A call from a caller to an interactive voice response (IVR) system may be serviced based on behavior by the caller in one or more prior calls to the IVR system. The call may be serviced by predicting information to be used in servicing the call. Predicting such information may include analyzing data reflecting behavior by the caller in one or more prior calls to the IVR system.
A call from a caller to an interactive voice response (IVR) system may be serviced based on behavior by the caller in one or more prior calls to the IVR system. The call may be serviced by predicting information to be used in servicing the call. Predicting such information may include analyzing data reflecting behavior by the caller in one or more prior calls to the IVR system.
Method And Apparatus For Generating Synthetic Speech With Contrastive Stress
Techniques for generating synthetic speech with contrastive stress. In one aspect, a speech-enabled application generates a text input including a text transcription of a desired speech output, and inputs the text input to a speech synthesis system. The synthesis system generates an audio speech output corresponding to at least a portion of the text input, with at least one portion carrying contrastive stress, and provides the audio speech output for the speech-enabled application. In another aspect, a speech-enabled application inputs a plurality of text strings, each corresponding to a portion of a desired speech output, to a software module for rendering contrastive stress. The software module identifies a plurality of audio recordings that render at least one portion of at least one of the text strings as speech carrying contrastive stress. The speech-enabled application generates an audio speech output corresponding to the desired speech output using the audio recordings.
Method And Apparatus For Generating Synthetic Speech With Contrastive Stress
Techniques for generating synthetic speech with contrastive stress. In one aspect, a speech-enabled application generates a text input including a text transcription of a desired speech output, and inputs the text input to a speech synthesis system. The synthesis system generates an audio speech output corresponding to at least a portion of the text input, with at least one portion carrying contrastive stress, and provides the audio speech output for the speech-enabled application. In another aspect, a speech-enabled application inputs a plurality of text strings, each corresponding to a portion of a desired speech output, to a software module for rendering contrastive stress. The software module identifies a plurality of audio recordings that render at least one portion of at least one of the text strings as speech carrying contrastive stress. The speech-enabled application generates an audio speech output corresponding to the desired speech output using the audio recordings.
- Cambridge MA, US Stuart R. Patterson - Hingham MA, US John Nguyen - Lexington MA, US Mark Alan Fanty - Norfolk MA, US Stephen R. Springer - Needham MA, US Erik Martin Gregory - Boston MA, US
Assignee:
The Affinity Project, Inc. - Cambridge MA
International Classification:
A61B 5/16 A61B 5/00 A61F 4/00 G06T 7/00 G06K 9/00
Abstract:
Assistance may be provided to a first user of a first device by monitoring sensors of the first device and providing assistance via a character presented by the device. Sensor data, such as audio, video, or biometric data, may be transmitted to a server, and a server may process the sensor data to determine a state of the first user. The server may determine to request assistance based on the state of the first user. The server may then send a request to a second device of a second user to guide the character presented by the first device. The second user may then provide assistance to the first user by guiding the character presented by the first device.
SpringCorps, Inc. since Oct 2012
Founder
SpringCorps, Inc. since Oct 2012
President & Ceo
Education:
Texas A&M University
Bachelor of Science (BS), Animal Sciences
Skills:
Team Building Powerpoint Public Speaking Windows Sales Teaching Event Planning English Negotiation Strategic Planning Sales Management Outlook Microsoft Office Microsoft Word Microsoft Excel Marketing Event Management Customer Service Budgets Non Profits Teamwork Project Management Public Relations Coaching Research Accounts Payable Access
Greenwood Southwest Elementary School Greenwood IN 1972-1975, Greenwood Middle School Greenwood IN 1976-1979, Central Nine Career Center High School Greenwood IN 1982-1984