Abstract: A portable electronic communication device, designed for voice and data communication is utilized as a peripheral input device for transmitting/providing character inputs, entered in the first device's touch input mechanism, to a second electronic device. The first device has a mode switching utility that switches the first device between a first standard communication mode and a second peripheral input device mode. When the first device is in the second peripheral input device mode, the first device operates as a peripheral input device for the second device.

Abstract: A method (600) and a system (102) for processing an incoming call (104). The method can include receiving the incoming call from a communication device (106, 108) and determining whether the communication device is configured to present a visual call menu. When the communication device is configured to present the visual call menu, the visual call menu can be communicated to the communication device. The present invention also relates to a method and a communication device for establishing a call. The method can include placing a call to a call handling system from a communication device, and receiving a visual call menu from the call handling system. The visual call menu can be presented on a display (120, 122, 508) associated with the communication device.

Abstract: A method and apparatus that stores information on a mobile communication device is disclosed. The method may include receiving a first signal from a user, initiating a recording of information spoken by at least one of the user, a voice mail recording, a recorded message, and a party engaged in the telephone call with the user based on the received first signal, receiving a second signal from the user, stopping the recording of the information based on the second signal being received, converting the recorded information to text, and storing the converted text to a designated location.

Abstract: A communication device includes: (1) a wireless adapter at which a wireless headset is communicatively connected to the communication device and at which is received a first acoustic input that includes a speech input and a first ambient noise input; (2) a microphone that receives a second acoustic input, which includes a second ambient noise input; and (3) a dual-channel adaptive noise canceller that utilizes the second ambient noise input to filter the first ambient noise input out of the first acoustic input to generate an acoustic output that primarily comprises the speech input.

Abstract: Speech presence is detected by first bandpass filtering (141, 143, 145) the speech to split it into banks of sub-bands. A matrix of shift registers (150) store each sub-band of speech. A power determining circuit (259) then determines individual power measurements of the speech stored in each shift register element. A variance combining circuit (160) combines the individual power measurements to provide a variance for the individual shift registers. A comparator circuit (170) finally compares the variance with at least one threshold to indicate whether speech is detected.

Abstract: A voice toolkit (100) and a method (700) for managing pronunciation dictionaries are provided. The visual toolkit can include a user-interface (110) for entering in a text and a corresponding spoken utterance, a text-to-speech system (120) for synthesizing a pronunciation from the text, a talking speech recognizer (132) for generating pronunciations of the spoken utterance, and a voice processor (130) for validating at least one pronunciation. A developer can type a text of a word into the toolkit and listen to the pronunciation to determine whether the pronunciation is acceptable. If the pronunciation is incorrect the developer can speak the word for providing a spoken utterance having a correct pronunciation.

Abstract: A system (100) and method (200) for generating a perturbed phonetic string for use in speech recognition. The method can include generating (202) a feature vector set from a spoken utterance, applying (204) a perturbation to the feature vector set for producing a perturbed feature vector set, and phonetically decoding (206) the perturbed feature vector set for producing a perturbed phonetic string. The perturbation mimics environmental variability and speaker variability for reducing the number of spoken utterances in speech recognition applications.

Abstract: A method and apparatus for speaker independent real-time affect detection includes generating (205) a sequence of audio frames from a segment of speech, generating (210) a sequence of feature sets by generating a feature set for each frame, and applying (215) the sequence of feature sets to a sequential classifier to determine a most likely affect expressed in the segment of speech.

Abstract: An electronic device (400) for speech dialog includes functions that receive (405, 205) a speech phrase that includes an instantiated variable (315), generate pitch and voicing characteristics (330) of the instantiated variable, and performs voice recognition (410, 220) of the instantiated variable to determine a most likely set of recognition acoustic states (335). A trained map (358) is established (115) that maps recognition feature vectors derived from training speech (105) to synthesis feature vectors derived from the same training speech (110). Recognition feature vectors that represent the most likely set of recognition acoustic states for the recognized instantiated variable are converted to a most likely set of synthesis acoustic states (420) in accordance with the map.

Abstract: A method and apparatus are provided for reproducing a speech sequence of a user through a communication device of the user. The method includes the steps of detecting a speech sequence from the user through the communication device, recognizing a phoneme sequence within the detected speech sequence and forming a confidence level of each phoneme within the recognized phoneme sequence. The method further includes the steps of audibly reproducing the recognized phoneme sequence for the user through the communication device and gradually highlighting or degrading a voice quality of at least some phonemes of the recognized phoneme sequence based upon the formed confidence level of the at least some phonemes.

Abstract: A method and apparatus is provided for identifying an input sequence entered by a user of a communication unit. The method includes the steps of providing a database containing a plurality of partial sequences from the user of the communication unit, recognizing an identity of at least some information items of the input sequence entered by the user, comparing the recognized sequence of information items with the plurality of partial sequences within the database and selecting a partial sequence of the plurality of sequences within the database with a closest relative match to the recognized sequence as the input sequence intended by the user.

Abstract: A method and apparatus for generating a voice tag (140) includes a means (110) for combining (205) a plurality of utterances (106, 107, 108) into a combined utterance (111) and a means (120) for extraction (210) of the voice tag as a sequence of phonemes having a high likelihood of representing the combined utterance, using a set of stored phonemes (115) and the combined utterance.

Abstract: An electronic device (300) for speech dialog includes functions that receive (305, 105) a speech phrase that comprises a request phrase that includes an instantiated variable (215), generate (335, 115) pitch and voicing characteristics (315) of the instantiated variable, and performs voice recognition (319, 125) of the instantiated variable to determine a most likely set of acoustic states (235). The electronic device may generate (335, 140) a synthesized value of the instantiated variable using the most likely set of acoustic states and the pitch and voicing characteristics of the instantiated variable. The electronic device may use a table of previously entered values of variables that have been determined to be unique, and in which the values are associated with a most likely set of acoustic states and the pitch and voicing characteristics determined at the receipt of each value to disambiguate (425, 430) a newly received instantiated variable.

Abstract: A system (100) for automatically discriminating information bearing audio segments and mere background noise segments processes digitized audio to extract two discriminants between information bearing audio and mere background audio that have a relatively low correlation. One discriminant is based on the rate (relative to the sample rate) at which a specified Boolean test involving sample values is met. Another possible discriminant is based on the variance of time-frequency magnitudes in a number of time windows and frequency bands. The two discriminants are suitably used as the independent variables of probability density functions that model information bearing audio and background noise audio.

Abstract: A method, a system and a computer program product for interpreting a verbal input in a multimodal dialog system are provided. The method includes assigning (302) a confidence value to at least one word generated by a verbal recognition component. The method further includes generating (304) a semantic unit confidence score for the verbal input. The generation of a semantic unit confidence score is based on the confidence value of at least one word and at least one semantic confidence operator.

Abstract: A tailored speaker-independent voice recognition system has a speech recognition dictionary (360) with at least one word (371). That word (371) has at least two transcriptions (373), each transcription (373) having a probability factor (375) and an indicator (377) of whether the transcription is active. When a speech utterance is received (510), the voice recognition system determines (520, 530) the word signified by the speech utterance, evaluates (540) the speech utterance against the transcriptions of the correct word, updates (550) the probability factors for each transcription, and inactivates (570) any transcription that has an updated probability factor that is less than a threshold.

Abstract: In a speech recognition platform, a masking unit 17 can be utilized to mask noisy content within an audio sample. By masking such noise in a dynamic but predictable manner, valid content can be preserved while largely overcoming the random and detrimental presence of noise. In one embodiment, speech recognition features are extracted pursuant to a hierarchical process that localizes, at least to some extent, some of the resultant features from other resultant features. As a result, noisy or otherwise unreliable information corresponding to the audio sample will not be leveraged unduly across the entire feature set. In another embodiment, an average energy value for processed samples is calculated with individual energy values that are downwardly weighted when such individual energy values are likely representative of noise.

Abstract: A dictionary is comprised of a dendroid hierarchy of branches and nodes, wherein each node represents no more than one symbol (which symbol is to be converted to a corresponding sound) and wherein each such symbol as is represented at a given node has only one corresponding sound associated with that symbol at that node. In addition, many of the branches include a plurality of nodes representing a string of the symbols in a particular sequence. The dictionary is used to translate an input comprising a given integral sequence of the symbols into a corresponding integral sequence of sounds. This permits both method and apparatus to convert, for example, text to representative phonemes. Such phonemes can be used, amongst other purposes, to support synthesized speech production.

Abstract: The invention provides a Hidden Markov Model (132) based automated speech recognition system (100) that dynamically adapts to changing background noise by detecting long pauses in speech, and for each pause processing background noise during the pause to extract a feature vector that characterizes the background noise, identifying a Gaussian mixture component of noise states that most closely matches the extracted feature vector, and updating the mean of the identified Gaussian mixture component so that it more closely matches the extracted feature vector, and consequently more closely matches the current noise environment. Alternatively, the process is also applied to refine the Gaussian mixtures associated with other emitting states of the Hidden Markov Model.

Abstract: A spoken language system (100) includes a recognition component (120) that generates (220) a recognized sequence of words from a sequence of received spoken words, and assigns (225) a confidence score to each word in the recognized sequence of words. A presentation component (140) of the spoken language system adjusts (240) nominal acoustical properties of words in a presentation (142) of the recognized sequence of words, the adjustment performed according to the confidence score of each word. The adjustments include adjustments to acoustical features and acoustical contexts of words and groups of words in the presented sequence of words. The presentation component presents (245) the adjusted sequence of words.