Abstract: A method of performing a search of a database of speakers, includes: receiving a query speech sample spoken by a query speaker; deriving a query utterance from the query speech sample; extracting query utterance statistics from the query utterance; performing Kernelized Locality-Sensitive Hashing (KLSH) using a kernel function, the KLSH using as input the query utterance statistics and utterance statistics extracted from a plurality of utterances included in a database of speakers in order to select a subset of the plurality of utterances; and comparing, using an utterance comparison equation, the query utterance statistics to the utterance statistics for each utterance in the subset to generate a list of speakers from the database of utterances having a highest similarity to the query speaker.

Abstract: During operation, a “coarse search” stage applies variable-scale windowing on the query pitch contours to compare them with fixed-length segments of target pitch contours to find matching candidates while efficiently scanning over variable tempo differences and target locations. Because the target segments are of fixed-length, this has the effect of drastically reducing the storage space required in a prior-art method. Furthermore, by breaking the query contours into parts, rhythmic inconsistencies can be more flexibly handled. Normalization is also applied to the contours to allow comparisons independent of differences in musical key. In a “fine search” stage, a “segmental” dynamic time warping (DTW) method is applied that calculates a more accurate similarity score between the query and each candidate target with more explicit consideration toward rhythmic inconsistencies.

Abstract: A method and apparatus for textual searching of a database is provided herein. During operation a user will input a letter into a search engine. The search engine will score words based on the letter and display results of the highest-scored words. Another letter will again be received and the process repeated. In situations where titles are returned to the user, additional steps of associating the words with a title and scoring the title take place. The highest-scored titles are provided to the user as the displayed results.

Abstract: A method, system and communication device for enabling uniterm discovery from audio content and voice-to-voice searching of audio content stored on a device using discovered uniterms. Received audio/voice input signal is sent to a uniterm discovery and search (UDS) engine within the device. The audio data may be associated with other content that is also stored within the device. The UDS engine retrieves a number of uniterms from the audio data and associates the uniterms with the stored content. When a voice search is initiated at the device, the UDS engine generates a statistical latent lattice model from the voice query and scores the uniterms from the audio database against the latent lattice model. Following a further refinement, the best group of uniterms is then determined and segments of the stored audio data and/or other content corresponding to the best group of uniterms are outputted.

Abstract: A method, system and communication device for enabling voice-to-voice searching and ordered content retrieval via audio tags assigned to individual content, which tags generate uniterms that are matched against components of a voice query. The method includes storing content and tagging at least one of the content with an audio tag. The method further includes receiving a voice query to retrieve content stored on the device. When the voice query is received, the method completes a voice-to-voice search utilizing uniterms of the audio tag, scored against the phoneme latent lattice model generated by the voice query to identify matching terms within the audio tags and corresponding stored content. The retrieved content(s) associated with the identified audio tags having uniterms that score within the phoneme lattice model are outputted in an order corresponding to an order in which the uniterms are structured within the voice query.

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: During operation, a “coarse search” stage applies variable-scale windowing on the query pitch contours to compare them with fixed-length segments of target pitch contours to find matching candidates while efficiently scanning over variable tempo differences and target locations. Because the target segments are of fixed-length, this has the effect of drastically reducing the storage space required in a prior-art method. Furthermore, by breaking the query contours into parts, rhythmic inconsistencies can be more flexibly handled. Normalization is also applied to the contours to allow comparisons independent of differences in musical key. In a “fine search” stage, a “segmental” dynamic time warping (DTW) method is applied that calculates a more accurate similarity score between the query and each candidate target with more explicit consideration toward rhythmic inconsistencies.

Abstract: A search system will receive a voice query and use speech recognition with a predefined vocabulary to generate a textual transcription of the voice query. Queries are sent to a text search engine, retrieving multiple web page results for each of these initial text queries. The collection of the keywords is extracted from the resulting web pages and is phonetically indexed to form a voice query dependent and phonetically searchable index database. Finally, a phonetically-based voice search engine is used to search the original voice query against the voice query dependent and phonetically searchable index database to find the keywords and/or key phrases that best match what was originally spoken. The keywords and/or key phrases that best match what was originally spoken are then used as a final text query for a search engine. Search results from the final text query are then presented to the user.

Abstract: Disclosed is a method for parsing a verbal expression received from a user to determine whether or not the expression contains a multiple-goal command. Specifically, known techniques are applied to extract terms from the verbal expression. The extracted terms are assigned to categories. If two or more terms are found in the parsed verbal expression that are in associated categories and that do not overlap one another temporally, then the confidence levels of these terms are compared. If the confidence levels are similar, then the terms may be parallel entries in the verbal expression and may represent multiple goals. If a multiple-goal command is found, then the command is either presented to the user for review and possible editing or is executed. If the parsed multiple-goal command is presented to the user for review, then the presentation can be made via any appropriate interface including voice and text interfaces.

Abstract: A method and apparatus for ordering results from a query is provided herein. During operation, a spoken query is received and converted to a textual representation, such as a word lattice. Search strings are then created from the word lattice. For example a set search strings may be created from the N-grams, such as unigrams and bigrams, of the word lattice. The search strings may be ordered and truncated based on confidence values assigned to the n-grams by the speech recognition system. The set of search strings are sent to at least one search engine, and search results are obtained. The search results are then re-arranged or reordered based on a semantic similarity between the search results and the word lattice.

Abstract: A method and apparatus for textual searching of a database is provided herein. During operation a user will input a letter into a search engine. The search engine will score words based on the letter and display results of the highest-scored words. Another letter will again be received and the process repeated. In situations where titles are returned to the user, additional steps of associating the words with a title and scoring the title take place. The highest-scored titles are provided to the user as the displayed results.

Abstract: An electronic device including a processor communicably coupled to a display component wherein the processor is configured to generate and display an interactive icon on the display component. The interactive icon includes a primary item and at least one alternative item, and the processor is configured to visually prioritize the presentation of the primary item on the display component relative to the presentation of the alternative item.

Abstract: Disclosed are editing methods that are added to speech-based searching to allow users to better understand textual queries submitted to a search engine and to easily edit their speech queries. According to some embodiments, the user begins to speak. The user's speech is translated into a textual query and submitted to a search engine. The results of the search are presented to the user. As the user continues to speak, the user's speech query is refined based on the user's further speech. The refined speech query is converted to a textual query which is again submitted to the search engine. The refined results are presented to the user. This process continues as long as the user continues to refine the query. Some embodiments present the textual query to the user and allow the user to use both speech-based and non-speech-based tools to edit the textual query.

Abstract: Disclosed is a technique for presenting audible items to a user in a manner that allows the user to easily distinguish them and to select from among them. A number of audible items are rendered simultaneously to the user. To prevent the sounds from blending together into a sonic mishmash, some of the items are “conditioned” while they are being rendered. For example, one audible item might be rendered more quietly than another, or one item can be moved up in register compared with another. Some embodiments combine audible conditioning with visual avatars portrayed on, for example, a display screen of a user device. During the rendering, each audible item is paired with an avatar, the pairing based on some suitable criterion, such as a type of conditioning applied to the audible item. Audible spatial placement is mimicked by visual placement of the avatars on the user's display screen.

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 and apparatus for performing speech recognition receives an audio signal, generates a sequence of frames of the audio signal, transforms each frame of the audio signal into a set of narrow band feature vectors using a narrow passband, couples the narrow band feature vectors to a speech model, and determines whether the audio signal is a wide band signal. When the audio signal is determined to be a wide band signal, a pass band parameter of each of one or more passbands that are outside the narrow passband is generated for each frame and the one or more band energy parameters are coupled to the speech model.

Abstract: A method, system and communication device for enabling voice-to-voice searching and ordered content retrieval via audio tags assigned to individual content, which tags generate uniterms that are matched against components of a voice query. The method includes storing content and tagging at least one of the content with an audio tag. The method further includes receiving a voice query to retrieve content stored on the device. When the voice query is received, the method completes a voice-to-voice search utilizing uniterms of the audio tag, scored against the phoneme latent lattice model generated by the voice query to identify matching terms within the audio tags and corresponding stored content. The retrieved content(s) associated with the identified audio tags having uniterms that score within the phoneme lattice model are outputted in an order corresponding to an order in which the uniterms are structured within the voice query.

Abstract: A method, apparatus, and electronic device for voice navigation are disclosed. A voice input mechanism 310 may receive a verbal input from a user to a voice user interface program invisible to the user. A processor 104 may identify in a graphical user interface (GUI) a set of GUI items. The processor 104 may convert the set of GUI items to a set of voice searchable indices 400. The processor 104 may correlate a matching GUI item of the set of GUI items to a phonemic representation of the verbal input.

Abstract: A method, system and communication device for enabling uniterm discovery from audio content and voice-to-voice searching of audio content stored on a device using discovered uniterms. Received audio/voice input signal is sent to a uniterm discovery and search (UDS) engine within the device. The audio data may be associated with other content that is also stored within the device. The UDS engine retrieves a number of uniterms from the audio data and associates the uniterms with the stored content. When a voice search is initiated at the device, the UDS engine generates a statistical latent lattice model from the voice query and scores the uniterms from the audio database against the latent lattice model. Following a further refinement, the best group of uniterms is then determined and segments of the stored audio data and/or other content corresponding to the best group of uniterms are outputted.

Abstract: A method and apparatus for enabling multimodal tags in a communication device is disclosed. The method comprises receiving a first training signal and receiving a second training signal in conjunction with the first training signal. A multimodal tag is created to represent a combination of the first training signal and the second training signal and a function is associated with the created multimodal tag.