| 1. |
- Sällberg, Benny, et al.
(författare)
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Analog Circuit Implementation for Speech Enhancement Purposes
- 2004
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Konferensbidrag (refereegranskat)abstract
- Abstract—Human speech is the main method for personal communication. However, interfering noise could degrade the intelligibility of speech, eventually resulting in errors. Thus, efficient speech enhancement algorithms are needed for example in hand held battery powered hearing aids. This paper presents an implementation of a time domain method for speech enhancement purposes; the Adaptive Gain Equalizer. The implementation is carried out on a printed circuit board using common analog electronic components, and evaluated in real-time. The proposed solution advances in prolonged battery life time, high system bandwidth, and it neither quantizes nor digitalizes data as opposed to many digital solutions.
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| 2. |
- Westerlund, Nils, et al.
(författare)
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Adaptive Gain Equalizer for Speech Enhancement
- 2002
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This report presents a noise reduction method for speech communication where the input signal is divided into a number of subbands that are individually weighted in time domain according to the short time Signal-to-Noise Ratio estimate (SNR) in each subband at every time instant. Instead of focusing on suppression the noise, the method is focusing on speech enhancement. The method has proven to be advantageous since it offers low complexity, low delay and low distortion. Also, there is no need for a Voice Activity Detector (VAD). The method is stand-alone and works regardless of speech coding schemes and other surrounding adaptive systems.
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| 3. |
- Westerlund, Nils, et al.
(författare)
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In-Ear Microphone Equalization Exploiting an Active Noise Control
- 2001
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Konferensbidrag (refereegranskat)abstract
- A pair of ear-muffs that employs active noise control(ANC) for noise reduction, substantially reduces the influence of the low frequencies inside the cap. This implies an indirect high-pass filtering of the sound in the external auditory canal (EAC). This paper shows that the above mentioned high-pass filtering property is convenient when combining an ANC headset with an in-ear microphone (ear-mic) for communication purposes since the speech signal inside the EAC is a low-pass filtered version of the speech signal at the mouth. Hence, the in-ear speech signal is to some extent restored by the ANC high-pass filtering, the quality of the speech signal in the auditory canal is improved and the speech intelligibility is increased. The equalization will also decrease the demand of dynamic range and resolution of electronics used. By that, combining an active ear-muff with an ear-mic serves two purposes: Protecting the user from harmful noise and enables the user to communicate over some channel using the speech signal in the auditory canal.
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| 4. |
- Westerlund, Nils, et al.
(författare)
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In-Ear Microphone Hybrid Speech Enhancement
- 2002
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Konferensbidrag (refereegranskat)abstract
- This paper presents a novel speech enhancement approach for performing noise reduction in severely disturbed environments. A small microphone for communication purposes is placed inside the external auditory canal to pick up the speech signal originating from the speech production organ. The speech enhancement is achieved by using three different noise reduction methods: High frequencies are attenuated by passive absorbers, low frequency components are attenuated by employing active noise control and finally a broadband noise reduction is achieved by using spectral subtraction.
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| 5. |
- Westerlund, Nils, et al.
(författare)
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Low Distortion SNR–Based Speech Enhancement Employing Critical Band Filter Banks
- 2003
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Konferensbidrag (refereegranskat)abstract
- This paper presents a speech enhancement method for personal communication where the input signal is divided into a number of subbands that are individually and adaptively weighted in time domain according to a short term SNR estimate in each subband at every time instant. Hence the name Adaptive Gain Equalizer. The method is focused on speech enhancement, acting as a speech booster, and remains idle when the SNR in a particular subband is low. Hence, background artifacts are eliminated and there is no need for a Voice Activity Detector (VAD). This paper also presents a method for least squares design of nonuniformfilter banks for application in subband signal processing. Design objectives aim to optimize the filter bank frequency response while minimizing subband and output aliasing. Critical band filter banks with increasing bandwidth are designed and evaluated with the speech enhancement method.
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| 6. |
- Westerlund, Nils, et al.
(författare)
-
Real-Time Implementation of an Adaptive Gain Equalizer for Speech Enhancement Purposes
- 2003
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a real time low-complexity implementation of a noise reduction method for speech communication where the input signal is divided into a number of subbands that are individually weighted in time domain according to the short timeS ignal-to-Noise Ratio estimate (SNR) in each subband at every time instant. Instead of focusing on suppression the noise, the method is focusing on speech enhancement. The method has proven to be advantageous when implemented in real time since it offers low complexity, low delay and low distortion.
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| 7. |
- Westerlund, Nils, et al.
(författare)
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Speech Enhancement by Non-Stationary Tonal Disturbance Cancellation using Subband Zero Crossing Measures
- 2004
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Konferensbidrag (refereegranskat)abstract
- A time domain based method for rejection of tonal disturbances in speech signals is presented. Tonal disturbances in personal communication arise in a variety of situations such as environmental sounds from rotating machinery, acoustic feedback in PA-systems or hearing aids and internal circuitry of some personal communication devices. The method is based on the zero crossings of subband signals. After splitting the disturbed signal into subbands, the distances between zero crossings in the subband signals are measured. A low distance spread indicates that a tonal component is dominating the subband signal. This distance spread is then used to steer a gain function that adaptively and continuously attenuates subbands in which tonal components are dominant. The method has proven to be effective on stationary as well as non-stationary disturbances with reasonable amount of speech signal distortion.
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| 8. |
- Westerlund, Nils, et al.
(författare)
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Speech Enhancement using an Adaptive Gain Equalizer
- 2003
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Konferensbidrag (refereegranskat)abstract
- This paper presents a noise reduction method forspeech communication where the input signal is divided into a number of subbands that are individually weighted in time domain according to the short time Signal-to-Noise Ratio estimate (SNR) in each subband at every time instant. Instead of focusing on suppression the noise, the method is focusing on speech enhancement. The method has proven to be advantageous since it offers low complexity, low delay and low distortion. Also, there is no need for a Voice Activity Detector (VAD). The method is stand-alone and works regardless of speech coding schemes and other surrounding adaptive systems.
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| 9. |
- Westerlund, Nils, et al.
(författare)
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Speech Enhancement using an Adaptive Gain Equalizer with Frequency Dependent Parameter Settings
- 2004
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Konferensbidrag (refereegranskat)abstract
- This paper presents an enhanced noise reduction method for speech communication where the input signal is divided into a number of subbands that are individually weighted in time domain according to the short time Signal-to-Noise Ratio estimate (SNR) in each subband at every time instant. Instead of focusing on suppression the noise, the method is focusing on speech enhancement. The subband based method is extended with frequency dependent parameter settings, equipping the user with further tweaking possibilities. Hence, making the algorithm even more versatile and applicable in different noise situations. The method has proven to be advantageous since it offers low complexity, low delay and low distortion. Also, there is no need for a Voice Activity Detector (VAD). The method is stand-alone and works regardless of speech coding schemes and other surrounding adaptive systems.
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| 10. |
- Westerlund, Nils, et al.
(författare)
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Speech Recognition in Severely Disturbed Environments Combining Ear-Mic and Active Noise Control
- 2002
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Konferensbidrag (refereegranskat)abstract
- A microphone for personal communication is placed inside the external auditory canal of a user. A pair of ear-muffs equippedwith Active Noise Control (ANC) are fitted onto the head of the user. The combination of passive and active noise reduction makes communication more reliable when performed in noisy environments. In this paper, a Hidden Markov Model (HMM) speech recognition system is used to assess the quality of speech signals recorded using an ear-mic combined with ANC. In addition, speech recognition itself can be of interest in many situations. For example, many functions in a vehicle can be controlled by instructions spoken by the user and speech controlled functionality improves safety. Hence, speech recognition is a growing field in vehicular technology. If the speech intelligibility and by that the speech recognition robustness could be increased in a speech recognition controlled system implemented in a vehicle, the safety would be further improved.
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