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7826 results about "Speech recognition" patented technology

Speech recognition is a interdisciplinary subfield of computational linguistics that develops methodologies and technologies that enables the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the linguistics, computer science, and electrical engineering fields.

System and methods for recognizing sound and music signals in high noise and distortion

A method for recognizing an audio sample locates an audio file that most closely matches the audio sample from a database indexing a large set of original recordings. Each indexed audio file is represented in the database index by a set of landmark timepoints and associated fingerprints. Landmarks occur at reproducible locations within the file, while fingerprints represent features of the signal at or near the landmark timepoints. To perform recognition, landmarks and fingerprints are computed for the unknown sample and used to retrieve matching fingerprints from the database. For each file containing matching fingerprints, the landmarks are compared with landmarks of the sample at which the same fingerprints were computed. If a large number of corresponding landmarks are linearly related, i.e., if equivalent fingerprints of the sample and retrieved file have the same time evolution, then the file is identified with the sample. The method can be used for any type of sound or music, and is particularly effective for audio signals subject to linear and nonlinear distortion such as background noise, compression artifacts, or transmission dropouts. The sample can be identified in a time proportional to the logarithm of the number of entries in the database; given sufficient computational power, recognition can be performed in nearly real time as the sound is being sampled.

Personalized audio system and method

A personalized audio system and method that overcomes many of the broadcast-type disadvantages associated with conventional radio stations. According to one embodiment, the personalized audio system includes the following: (1) a user interface that enables a user of the personalized audio system to specify a profile for a personalized audio channel, (2) a sound recording library comprising a plurality of sound recordings, (3) a playlist generator that (a) selects a plurality of sound recording identifiers from a set of sound recording identifiers, wherein each of the plurality of sound recording identifiers identifies a sound recording that matches the profile and that is stored in the library, and that (b) creates a playlist that lists the plurality of sound recording identifiers in a particular order, and (4) a sound recording reproducing device for reproducing the plurality of identified sound recordings according to the particular order in which the sound recording identifiers are listed in the playlist so that the user can listen to the sound recordings. Advantageously, the personalized audio system does not provide the user with a way to determine the plurality of sound recording identifiers prior to the reproducing means reproducing the plurality of sound recordings, and the personalized audio system does not provide the user with a way to directly control which sound recording identifiers in the set are selected by the playlist generator to be included in the plurality of sound recording identifiers.

Method and apparatus for automatically identifying and selectively altering segments of a television broadcast signal in real-time

The method and apparatus identifies selected broadcast segments, such as commercial advertisements, of a television signal in real-time for the purpose of muting the video and audio portions of the television signal during each unwanted segment. A signature pattern associated with each segment of the television signal is detected and compared to stored signature patterns representative of selected segments such as commercial advertisement segments. If the signature pattern matches one of the stored signature patterns, the segment is thereby immediately identified as being one of the selected segments and is processed in real-time to mute the audio and video portions of the television signal during the segment. If the signature pattern of the segment does not match any of the stored signature patterns, the segment is analyzed to determine whether the segment is nevertheless a selected segment and, if so, its signature pattern is stored along with the stored signature patterns. The analysis to determine whether the segment is nevertheless a selected segment is performed by detecting the length of the segment upon its completion and then determining whether the length of the segment matches one of a pre-determined set of permissible selected segment lengths such as standard commercial advertisement segments of 15 seconds, 30 seconds, or 60 seconds. If so, the segment is identified as being a selected and its signature pattern is stored along with the other stored signature patterns such that, the next time the same segment is encountered, its signature will then match the stored signature and therefore the segment can be immediately identified and muted in real-time.
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