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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

Kurtosis-Controlled Babble Noise Suppression

When a speech application is employed in a crowded environment, the user’s voice superposes with many interfering voices. This babble noise is a challenge for

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Voice Activity Detection Based on Modulation-Phase Differences

Many speech processing algorithms rely on voice activity detection (VAD) that separates speech from noise. For this task, several features have been introduced that employ

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A single-channel non-intrusive C50 estimator correlated with speech recognition performance

Abstract—Several intrusive measures of reverberation can be computed from measured and simulated room impulse responses, over the full frequency band or for each individual mel-frequency

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Statistical Signal Processing Techniques for Robust Speech Recognition

Automatic speech recognition is becoming increasingly more important, with commercial applications such as call steering, dictation or voice-enabled personal assistance systems. Although successful in many

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Features for voice activity detection: a comparative analysis

In many speech signal processing applications, voice activity detection (VAD) plays an essential role for separating an audio stream into time intervals that contain speech

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Listening Test to Determine the Mismatch Between Signal-to-Noise Ratio and Human Perception

Evaluations of speech enhancement systems are typically based on artificially generated noisy speech signals. A common approach to quantify the weighting of speech and background

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Effects of resampling in acoustic echo cancellation with static nonlinear loudspeaker distortion

In modern acoustic echo compensation (AEC), nonlinear models are applied to mimic the loudspeaker’s behavior. Many conventional methods disregard the NYQUIST criterion when applying the

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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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Improved performance measures for voice activity detection

Voice activity detection is an essential part of many speech processing algorithms. The requirements of the speech application determine the design of voice activity detection.

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