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| Application No. | Application Title | Issue Date |
| 20110071835 | SMALL FOOTPRINT TEXT-TO-SPEECH ENGINE Embodiments of small footprint text-to-speech engine are disclosed. In operation, the small footprint text-to-speech engine generates a set of feature parameters for an input text. The set of feature parameters includes static feature parameters and delta feature parame... | 03/24/2011 |
| 20110015925 | SPEECH RECOGNITION SYSTEM AND METHOD A speech recognition method, comprising:
| 01/20/2011 |
| 20110010176 | HMM LEARNING DEVICE AND METHOD, PROGRAM, AND RECORDING MEDIUM An HMM (Hidden Markov Model) learning device includes: a learning unit for learning a state transition probability as the function of actions that an agent can execute, with learning with HMM performed based on actions that the agent has executed, and time series inform... | 01/13/2011 |
| 20100318354 | NOISE ADAPTIVE TRAINING FOR SPEECH RECOGNITION Technologies are described herein for noise adaptive training to achieve robust automatic speech recognition. Through the use of these technologies, a noise adaptive training (NAT) approach may use both clean and corrupted speech for training. The NAT approach may norma... | 12/16/2010 |
| 20100312562 | HIDDEN MARKOV MODEL BASED TEXT TO SPEECH SYSTEMS EMPLOYING ROPE-JUMPING ALGORITHM A rope-jumping algorithm is employed in a Hidden Markov Model based text to speech system to determine start and end models and to modify the start and end models by setting small co-variances. Disordered acoustic parameters due to violation of parameter constraints are... | 12/09/2010 |
| 20100204988 | SPEECH RECOGNITION METHOD A speech recognition method includes receiving a speech input signal in a first noise environment which includes a sequence of observations, determining the likelihood of a sequence of words arising from the sequence of observations using an acoustic model, adapting the... | 08/12/2010 |
| 20100191532 | Model-based comparative measure for vector sequences and word spotting using same An object comparison method comprises: generating a first ordered vector sequence representation of a first object; generating a second ordered vector sequence representation of a second object; representing the first object by a first ordered sequence of model paramete... | 07/29/2010 |
| 20100128985 | ONLINE ARABIC HANDWRITING RECOGNITION Method for online character recognition of Arabic text, the method including receiving handwritten Arabic text from a user in the form of handwriting strokes, sampling the handwriting strokes to acquire a sequence of two dimensional point representations thereof, with a... | 05/27/2010 |
| 20100070280 | PARAMETER CLUSTERING AND SHARING FOR VARIABLE-PARAMETER HIDDEN MARKOV MODELS A speech recognition system uses Gaussian mixture variable-parameter hidden Markov models (VPHMMs) to recognize speech. The VPHMMs include Gaussian parameters that vary as a function of at least one environmental conditioning parameter. The relationship of each Gaussian... | 03/18/2010 |
| 20090112595 | DISCRIMINATIVE TRAINING OF MULTI-STATE BARGE-IN MODELS FOR SPEECH PROCESSING Disclosed are systems and methods for training a barge-in-model for speech processing in a spoken dialogue system comprising the steps of (1) receiving an input having at least one speech segment and at least one non-speech segment, (2) establishing a restriction of rec... | 04/30/2009 |
| 20090055182 | Discriminative Training of Hidden Markov Models for Continuous Speech Recognition Methods are given for improving discriminative training of hidden Markov models for continuous speech recognition. For a mixture component of a hidden Markov model state, a gradient adjustment is calculated of the standard deviation of the mixture component. If the calc... | 02/26/2009 |
| 20080147404 | System and methods for accent classification and adaptation Speech is processed that may be colored by speech accent. A method for recognizing speech includes maintaining a model of speech accent that is established based on training speech data, wherein the training speech data includes at least a first set of training speech d... | 06/19/2008 |
