Abstract: The subject matter discloses a computerized method for sales optimization comprising: receiving at a computer server a digital representation of a portion of an interaction between a customer and an organization representative, the portion of an interaction comprises a speech signal of the customer and a speech signal of the organization representative; analyzing the speech signal of the organization representative; analyzing the speech signal of the customer; determining a distance vector between the speech signal of the organization representative and the speech signal of the customer; and predicting a sale success probability score for the captured speech signal portion.

Abstract: A method for automatic speech recognition includes determining for an input signal a plurality scores representative of certainties that the input signal is associated with corresponding states of a speech recognition model, using the speech recognition model and the determined scores to compute an average signal, computing a difference value representative of a difference between the input signal and the average signal, and processing the input signal in accordance with the difference value.

Abstract: Disclosed herein are an apparatus and method for recognizing speech. The apparatus includes a frame-based speech recognition unit, a segment division unit, a segment feature extraction unit, a segment speech recognition performance unit, and a combination and synchronization unit. The frame-based speech recognition unit extracts frame speech feature vectors from a speech signal, and performs speech recognition on frames of the speech signal using the frame speech feature vectors and a frame-based probability model. The segment division unit divides the speech signal into segments. The segment feature extraction unit extracts segment speech feature vectors around a boundary between the segments. The segment speech recognition performance unit performs speech recognition on the segments of the speech signal using the segment speech feature vectors and a segment-based probability model.

Abstract: A novel beamforming post-processor technique with enhanced noise suppression capability. The present beam forming post-processor technique is a non-linear post-processing technique for sensor arrays (e.g., microphone arrays) which improves the directivity and signal separation capabilities. The technique works in so-called instantaneous direction of arrival space, estimates the probability for sound coming from a given incident angle or look-up direction and applies a time-varying, gain based, spatio-temporal filter for suppressing sounds coming from directions other than the sound source direction resulting in minimal artifacts and musical noise.

Abstract: According to one embodiment of the invention, a method classifying a number of noun phrases in a first text passage and a second text passage into a number of classifications. The method also includes determining a similarity between a noun phrase from the first text passage and a noun phase from the second text passage for each of the noun phrases of a same classification. Additionally, a similarity between a sentence from the first text passage and a sentence from the second text passage is determined for each of the sentences in the first and second text passages based on similarities between the noun phrases. The method also includes determining a similarity between the first text passage and the second text passage based on a similarities between sentences.

Abstract: A method and system for improving the efficiency of real-time and non-real-time speech transcription by machine speech recognizers, human dictation typists, and human voicewriters using speech recognizers. In particular, the pacing with which recorded speech is presented to transcriptionists is automatically adjusted by monitoring the transcriptionists' output by comparing the output acoustically or phonetically to the presented recorded speech as well as monitoring the resulting transcription, and accordingly adjusting the pacing.

Abstract: A speech recognition apparatus capable of attaining high recognition accuracy within practical processing time using a computing machine having standard performance by appropriately adapting a language model to a speech about a certain topic, irrespectively of a degree of detail and diversity of the topic and irrespectively of a confidence score of an initial speech recognition result is provided.

Abstract: A speech recognition circuit comprising a circuit for providing state identifiers which identify states corresponding to nodes or groups of adjacent nodes in a lexical tree, and for providing scores corresponding to said state identifiers, the lexical tree comprising a model of words; a memory structure for receiving and storing state identifiers identified by a node identifier identifying a node or group of adjacent nodes, said memory structure being adapted to allow lookup to identify particular state identifiers, reading of the scores corresponding to the state identifiers, and writing back of the scores to the memory structure after modification of the scores; an accumulator for receiving score updates corresponding to particular state identifiers from a score update generating circuit which generates the score updates using audio input, for receiving scores from the memory structure, and for modifying said scores by adding said score updates to said scores; and a selector circuit for selecting at least o

Abstract: Improvement in the reliability of segmentation of a signal, such as an ECG signal, is disclosed through the use of duration constraints. The signal is analysed using a hidden Markov model. The duration constraints specify minimum allowed durations for specific states of the model. The duration constraints can be incorporated either in the model itself or in a Viterbi algorithm used to compute the most probable state sequence given a conventional model. Also disclosed is the derivation of a confidence measure from the model which can be used to assess the quality and robustness of the segmentation and to identify any signals for which the segmentation is unreliable, for example due to the presence of noise or abnormality in the signal.

Abstract: An information processing apparatus whereby advice having appropriate content can be given at an appropriate timing with regard to a method of user utterance, thereby making it possible to reduce the probability of misrecognition due to the method of utterance. An execution unit executes processing that conforms to the result of speech recognition. An analyzing unit analyzes the suitability of input speech for the speech recognition. A cancel instruction unit inputs an instruction to cancel the processing that has been executed by the execution unit. In response to the cancel instruction, a notification unit notifies the user of guidance related to speech input, based upon the result of the analysis unit.