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Speech enhancement

Speech enhancement is focused on evolving the technologies used in voice-driven interfaces for an enhanced user experience and greater application flexibility for manufacturers.

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Speech enhancement



Leading the industry in speech technology
Nuance’s speech enhancement group in Ulm, Germany, has been a research leader in the field of speech and audio signal processing for over 15 years. The team provides custom-tailored solutions for robust speech recognition and enhanced speech communication across many platforms and in a variety of environments. Our core research competencies include:

  • Single-microphone noise reduction approaches
  • Acoustic echo cancellation for voice user interfaces and telecommunication
  • Cutting-edge spatial filtering techniques for beam forming and interference cancellation

Using speech to enhance user-experience in other industries
Our research also encompasses more diverse speech enhancement topics such as speech reconstruction, bandwidth extension, dynamic signal mixing, or adaptive equalization. These efforts have resulted in an integrated speech enhancement front-end, which is deployed in various automotive, home, and mobile applications.
Our technology supports speech interaction with virtual personal assistants, even in the most challenging acoustic environments. As a leading expert for automotive speech enhancement, we also provide solutions for high-quality hands-free telephony as well as systems to improve in-car communication between front and rear passengers in large sedans and vans.

Explore recent publications by Nuance Speech Enhancement researchers.



Selected articles

Simultaneous speech recognition and speaker identification

In this paper we present a self-learning speech controlled system comprising speech recognition, speaker identification and speaker adaptation for a small number of users, e.g.

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Evaluation of two approaches for speaker specific speech recognition

In this paper we examine two approaches for the automatic personalization of speech controlled systems. Speech recognition may be significantly improved by continuous speaker adaptation

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Detection of unknown speakers in an unsupervised speech controlled system

In this paper we investigate the capability of our self-learning speech controlled system comprising speech recognition, speaker identification and speaker adaptation to detect unknown users.

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Speaker tracking in an unsupervised speech controlled system

In this paper we present a technique to increase the robustness of a self-learning speech controlled system comprising speech recognition, speaker identification and speaker adaptation.

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Fast adaptation of speech and speaker characteristics for enhanced speech recognition in adverse intelligent environments

In this paper we present a technique for fast adaptation of speech and speaker related information. Fast learning is particularly useful for automatic personalization of

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Robust voice activity detection for distributed microphones by modeling of power ratios

In this paper a method for a robust frequency selective voice activity detection (VAD) is presented that evaluates the power ratios between several distributed microphones.

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A subband based acoustic source localization system for reverberant environments

In this paper an efficient acoustic source localization sys­tem is described which works within a subband process­ing framework and is robust against reverberation. The proposed

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Spatial maximum a posteriori post-filtering for arbitrary beamforming

We present a new approach for residual transient noise suppression at the output of an arbitrary beamformer. A spatial optimum esti­mate for the instantaneous a

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Phoneme-dependent speech enhancement

The majority of current speech enhancement systems are based on generalized signal-to-noise ratio dependent weighting rules and do not take into account the characteristics of

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Acoustic array processing for speech enhancement

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