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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

Low-Complexity Pitch Estimation Based on Phase Differences Between Low-Resolution Spectra

Detection of voiced speech and estimation of the pitch frequency are important tasks for many speech processing algorithms. Pitch information can be used, e.g., to

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Detection of Voiced Speech and Pitch Estimation for Applications with Low Spectral Resolution

Speech enhancement algorithms are employed in many applications, such as hands-free telephones, or speech recognizers, to recover a speech signal that is recorded in a

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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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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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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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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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A morphological approach to single-channel wind-noise suppression

Today, a variety of technical devices deploy spoken language processing technology. In many practical use cases, not only stationary ambient noises but non-stationary interferences, such

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A practical beamformer-postfilter system for adaptive speech enhancement in non-stationary noise environments

In this contribution we present an adaptive beamformer-postfilter system which can be used to suppress non-stationary noises. The emphasis lies on the spatial filtering property

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