Abstract: The present invention provides systems and methods for signal detection and enhancement. The systems and methods utilize one or more discriminative classifiers (e.g., a logistic regression model and a convolutional neural network) to estimate a posterior probability that indicates whether a desired signal is present in a received signal. The discriminative estimators generate the estimated probability based on one or more signal-to-noise ratio (SNRs) (e.g., a normalized logarithmic posterior SNR (nlpSNR) and a mel-transformed nlpSNR (mel-nlpSNR)) and an estimated noise model. Depending on the resolution desired, the estimated SNR can be generated at a frame level or at an atom level, wherein the atom level estimates are utilized to generate the frame level estimate. The novel systems and methods can be utilized to facilitate speech detection, speech recognition, speech coding, noise adaptation, speech enhancement, microphone arrays and echo-cancellation.

Abstract: The present invention relates to a system and methodology to facilitate automatic management and pruning of audio files residing in a database. Audio fingerprinting is a powerful tool for identifying streaming or file-based audio, using a database of fingerprints. Duplicate detection identifies duplicate audio clips in a set, even if the clips differ in compression quality or duration. The present invention can be provided as a self-contained application that it does not require an external database of fingerprints. Also, a user interface provides various options for managing and pruning the audio files.

Abstract: The present invention relates to a system and methodology to facilitate automatic generation of mnemonic audio portions or segments referred to as audio thumbnails. A system is provided for summarizing audio information. The system includes an analysis component to determine common features in an audio file and a mnemonic detector to extract fingerprint portions of the audio file based in part on the common features in order to generate a thumbnail of the audio file. The generated thumbnails can then be employed to facilitate browsing or searching audio files in order to mitigate listening to longer portions or segments of such files.

Abstract: Information about media objects within media streams is inferred based on repeat instances of the media objects within the media streams. A system and methods enable the monitoring of one or more media streams and the identification of repeat instances of media objects (e.g., audio and/or video objects) within the media streams. The monitoring and object repeat identification is performed by one or more server computers on a network. Information about a media object can be inferred based on repeat instances of the media object and based on repeat instances of related media objects. The information is transferred from a server to a client in response to a user query entered at the client through an interactive user interface.

Abstract: The content of a media program is recognized by analyzing its audio content to extract therefrom prescribed features, which are compared to a database of features associated with identified content. The identity of the content within the database that has features that most closely match the features of the media program being played is supplied as the identity of the program being played. The features are extracted from a frequency domain version of the media program by a) filtering the coefficients to reduce their number, e.g., using triangular filters; b) grouping a number of consecutive outputs of triangular filters into segments; and c) selecting those segments that meet prescribed criteria, such as those segments that have the largest minimum segment energy with prescribed constraints that prevent the segments from being too close to each other. The triangular filters may be log-spaced and their output may be normalized.