Robust speech recognition by normalization of the acoustic space
14 Apr 1991-pp 893-896
TL;DR: Several algorithms are presented that increase the robustness of SPHINX, the CMU (Carnegie Mellon University) continuous-speech speaker-independent recognition systems, by normalizing the acoustic space via minimization of the overall VQ distortion.
Abstract: Several algorithms are presented that increase the robustness of SPHINX, the CMU (Carnegie Mellon University) continuous-speech speaker-independent recognition systems, by normalizing the acoustic space via minimization of the overall VQ distortion. The authors propose an affine transformation of the cepstrum in which a matrix multiplication perform frequency normalization and a vector addition attempts environment normalization. The algorithms for environment normalization are efficient and improve the recognition accuracy when the system is tested on a microphone other than the one on which it was trained. The frequency normalization algorithm applies a different warping on the frequency axis to different speakers and it achieves a 10% decrease in error rate. >
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Patent•
11 Jan 2011TL;DR: In this article, an intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions.
Abstract: An intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.
1,462 citations
Patent•
19 Oct 2007TL;DR: In this paper, various methods and devices described herein relate to devices which, in at least certain embodiments, may include one or more sensors for providing data relating to user activity and at least one processor for causing the device to respond based on the user activity which was determined, at least in part, through the sensors.
Abstract: The various methods and devices described herein relate to devices which, in at least certain embodiments, may include one or more sensors for providing data relating to user activity and at least one processor for causing the device to respond based on the user activity which was determined, at least in part, through the sensors. The response by the device may include a change of state of the device, and the response may be automatically performed after the user activity is determined.
844 citations
Patent•
28 Sep 2012TL;DR: In this article, a virtual assistant uses context information to supplement natural language or gestural input from a user, which helps to clarify the user's intent and reduce the number of candidate interpretations of user's input, and reduces the need for the user to provide excessive clarification input.
Abstract: A virtual assistant uses context information to supplement natural language or gestural input from a user. Context helps to clarify the user's intent and to reduce the number of candidate interpretations of the user's input, and reduces the need for the user to provide excessive clarification input. Context can include any available information that is usable by the assistant to supplement explicit user input to constrain an information-processing problem and/or to personalize results. Context can be used to constrain solutions during various phases of processing, including, for example, speech recognition, natural language processing, task flow processing, and dialog generation.
593 citations
TL;DR: After training on clean speech data, the performance of the recognizer was found to be severely degraded when noise was added to the speech signal at between 10 and 18 dB, but using PMC the performance was restored to a level comparable with that obtained when training directly in the noise corrupted environment.
Abstract: This paper addresses the problem of automatic speech recognition in the presence of interfering noise. It focuses on the parallel model combination (PMC) scheme, which has been shown to be a powerful technique for achieving noise robustness. Most experiments reported on PMC to date have been on small, 10-50 word vocabulary systems. Experiments on the Resource Management (RM) database, a 1000 word continuous speech recognition task, reveal compensation requirements not highlighted by the smaller vocabulary tasks. In particular, that it is necessary to compensate the dynamic parameters as well as the static parameters to achieve good recognition performance. The database used for these experiments was the RM speaker independent task with either Lynx Helicopter noise or Operation Room noise from the NOISEX-92 database added. The experiments reported here used the HTK RM recognizer developed at CUED modified to include PMC based compensation for the static, delta and delta-delta parameters. After training on clean speech data, the performance of the recognizer was found to be severely degraded when noise was added to the speech signal at between 10 and 18 dB. However, using PMC the performance was restored to a level comparable with that obtained when training directly in the noise corrupted environment.
509 citations
Cites background from "Robust speech recognition by normal..."
...Additionally, techniques have attempted to estimate the clean speech under additive and convolutional noise conditions [1]....
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Patent•
08 Sep 2006TL;DR: In this paper, a method for building an automated assistant includes interfacing a service-oriented architecture that includes a plurality of remote services to an active ontology, where the active ontologies includes at least one active processing element that models a domain.
Abstract: A method and apparatus are provided for building an intelligent automated assistant. Embodiments of the present invention rely on the concept of “active ontologies” (e.g., execution environments constructed in an ontology-like manner) to build and run applications for use by intelligent automated assistants. In one specific embodiment, a method for building an automated assistant includes interfacing a service-oriented architecture that includes a plurality of remote services to an active ontology, where the active ontology includes at least one active processing element that models a domain. At least one of the remote services is then registered for use in the domain.
389 citations
References
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TL;DR: A stand-alone noise suppression algorithm that resynthesizes a speech waveform and can be used as a pre-processor to narrow-band voice communications systems, speech recognition systems, or speaker authentication systems.
Abstract: A stand-alone noise suppression algorithm is presented for reducing the spectral effects of acoustically added noise in speech. Effective performance of digital speech processors operating in practical environments may require suppression of noise from the digital wave-form. Spectral subtraction offers a computationally efficient, processor-independent approach to effective digital speech analysis. The method, requiring about the same computation as high-speed convolution, suppresses stationary noise from speech by subtracting the spectral noise bias calculated during nonspeech activity. Secondary procedures are then applied to attenuate the residual noise left after subtraction. Since the algorithm resynthesizes a speech waveform, it can be used as a pre-processor to narrow-band voice communications systems, speech recognition systems, or speaker authentication systems.
4,862 citations
03 Apr 1990
TL;DR: Initial efforts to make Sphinx, a continuous-speech speaker-independent recognition system, robust to changes in the environment are reported, and two novel methods based on additive corrections in the cepstral domain are proposed.
Abstract: Initial efforts to make Sphinx, a continuous-speech speaker-independent recognition system, robust to changes in the environment are reported. To deal with differences in noise level and spectral tilt between close-talking and desk-top microphones, two novel methods based on additive corrections in the cepstral domain are proposed. In the first algorithm, the additive correction depends on the instantaneous SNR of the signal. In the second technique, expectation-maximization techniques are used to best match the cepstral vectors of the input utterances to the ensemble of codebook entries representing a standard acoustical ambience. Use of the algorithms dramatically improves recognition accuracy when the system is tested on a microphone other than the one on which it was trained. >
461 citations
01 Apr 1975
TL;DR: In this paper, the blind deconvolution problem of two signals when both are unknown is addressed and two related solutions which can be applied through digital signal processing in certain practical cases are discussed.
Abstract: This paper addresses the problem of deconvolving two signals when both are unknown. The authors call this problem blind deconvolution. The discussion develops two related solutions which can be applied through digital signal processing in certain practical cases. The case of reverberated and resonated sound forms the center of the development. The specific problem of restoring old acoustic recordings provides an experimental test. The important effects of noise and non-stationary signals lead to the detailed part of the presentation. In addition, the paper presents results for the case of images degraded by some common forms of blur.
370 citations
TL;DR: A bank of critical-band filters defines the initial spectral analysis, and filter outputs are processed by a model of the nonlinear transduction stage in the cochlea, which accounts for such features as saturation, adaptation and forward masking.
264 citations
01 Jun 1972
TL;DR: The requirements for digital sequences by other digital sequences and the use of such representations to implement a nonlinear warping of the digital frequency axis are discussed within the framework of simulating linear time-invariant systems.
Abstract: In processing continuous-time signals by digitalmeans, it is necessary to represent the signal by a digital sequence. There are many ways other than periodic sampling for obtaining such a sequence. The requirements for such representations and some examples are discussed within the framework of simulating linear time-invariant systems. The representation of digital sequences by other digital sequences is also discussed, with particular emphasis on the use of such representations to implement a nonlinear warping of the digital frequency axis. Some applications and hardware implementation of this digital-frequency warping are described.
219 citations