Abstract: An exemplary noise reduction system and method processes a speech signal that is delivered in a noisy channel or with ambient noise. Some exemplary embodiments of the system and method use filters to extract speech information, and focus on a subset of harmonics that are least corrupted by noise. Some exemplary embodiments disregard signal harmonics with low signal-to-noise ratio(s), and disregard amplitude modulations that are inconsistent with speech. An exemplary system and method processes a signal that focuses on a subset of harmonics that are least corrupted by noise, disregards the signal harmonics with low signal-to-noise ratio(s), and disregards amplitude modulations that are inconsistent with speech.

Abstract: An exemplary noise reduction system and method processes a speech signal that is delivered in a noisy channel or with ambient noise. Some exemplary embodiments of the system and method use filters to extract speech information, and focus on a subset of harmonics that are least corrupted by noise. Some exemplary embodiments disregard signal harmonics with low signal-to-noise ratio(s), and disregard amplitude modulations that are inconsistent with speech. An exemplary system and method processes a signal that focuses on a subset of harmonics that are least corrupted by noise, disregards the signal harmonics with low signal-to-noise ratio(s), and disregards amplitude modulations that are inconsistent with speech.

Abstract: An exemplary noise reduction system and method processes a speech signal that is delivered in a noisy channel or with ambient noise. Some exemplary embodiments of the system and method use filters to extract speech information, and focus on a subset of harmonics that are least corrupted by noise. Some exemplary embodiments disregard signal harmonics with low signal-to-noise ratio(s), and disregard amplitude modulations that are inconsistent with speech. An exemplary system and method processes a signal that focuses on a subset of harmonics that are least corrupted by noise, disregards the signal harmonics with low signal-to-noise ratio(s), and disregards amplitude modulations that are inconsistent with speech.

Abstract: Speech recognition is performed in near-real-time and improved by exploiting events and event sequences, employing machine learning techniques including boosted classifiers, ensembles, detectors and cascades and using perceptual clusters. Speech recognition is also improved using tandem processing. An automatic punctuator injects punctuation into recognized text streams.