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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

Adaptive receive side equalization for improved intelligibility in automotive hands-free systems

The intelligibility of the received audio signal in automotive hands-free systems typically suffers from limited bandwidth as well as from being rendered in noisy environment.

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Entwurf und analyse von beamformer-nachfilter-systemen

PhD Thesis

A generalized view on microphone array postfilters

In this paper a generic transfer function for microphone array postfilters is derived and discussed. This function comprises a matrix which can be designed freely

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Robust Pitch Tracking in the Car Environment

In this paper, we compare four different pitch tracking algorithms – autocorrelation, cepstrum, harmonic product spectrum, and a new method based on the modulation spectrum

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Grundfrequenzbestimmung aus dem Modulationsspektrum
Absolute Perceived Loudness of Speech

A number of speech samples recorded with different amplifier gain are subjected to a psychoacoustic loudness model developed for this project. For this, the recordings are normalized

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Speaker activity detection for distributed microphone systems in cars

In this contribution a new framework for energy-based acoustic speaker activity detection for distributed microphones in automotive environments is presented. The method relies on the

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Robust adaptive cancellation of interfering speakers for distributed microphone systems in cars

Hands-free systems in cars aim to capture the speech of different speakers at the best. Therefor distributed microphones can be aligned to each of these

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Efficient multi-channel acoustic echo cancellation using constrained sparse filter updates in the subband domain

In this paper we present constrained sparse tap-selection schemes for updating Multi-Channel Acoustic Echo Can­cellation (MAEC) filters in the subband domain. We per­form M-Max tap-selection

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Detection of local disturbances and simultaneously active speakers for distributed speaker-dedicated microphones in cars

For automotive hands-free and speech recognition applications, distributed microphones are often mounted in the car where each of the speakers has a dedicated microphone close

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