P. Mueller

A foveated silicon retina for two-dimensional tracking

A silicon retina chip with a central foveal region for smooth-pursuit tracking and a peripheral region for saccadic target acquisition is presented. The foveal region contains a 9/spl times/9 dense array of large dynamic range photoreceptors and edge detectors. Two-dimensional direction of foveal motion is computed outside the imaging array. The peripheral region contains a sparse array of 19/spl times/17 similar, but larger, photoreceptors with in-pixel edge and temporal on-set detection. The coordinates of moving or flashing targets are computed with two one-dimensional centroid localization circuits located on the outskirts of the peripheral region. The chip is operational for ambient intensities ranging over six orders of magnitude, targets contrast as low as 10%, foveal speed ranging from 1.5 to 10 K pixels/s, and peripheral ON-set frequencies from <0.1 to 800 kHz. The chip is implemented in a 2 /spl mu/m n-well CMOS process and consumes 15 mW (Vdd=4 V) in normal indoor light (25 /spl mu/W/cm/sup 2/). It has been used as a person tracker in a smart surveillance system and a road follower in an autonomous navigation system.

Nonparallel training for voice conversion based on a parameter adaptation approach

The objective of voice conversion algorithms is to modify the speech by a particular source speaker so that it sounds as if spoken by a different target speaker. Current conversion algorithms employ a training procedure, during which the same utterances spoken by both the source and target speakers are needed for deriving the desired conversion parameters. Such a (parallel) corpus, is often difficult or impossible to collect. Here, we propose an algorithm that relaxes this constraint, i.e., the training corpus does not necessarily contain the same utterances from both speakers. The proposed algorithm is based on speaker adaptation techniques, adapting the conversion parameters derived for a particular pair of speakers to a different pair, for which only a nonparallel corpus is available. We show that adaptation reduces the error obtained when simply applying the conversion parameters of one pair of speakers to another by a factor that can reach 30%. A speaker identification measure is also employed that more insightfully portrays the importance of adaptation, while listening tests confirm the success of our method. Both the objective and subjective tests employed, demonstrate that the proposed algorithm achieves comparable results with the ideal case when a parallel corpus is available.

An analog neural computer with modular architecture for real-time dynamic computations

A multichip analog parallel neural network whose architecture, neuron characteristics, synaptic connections, and time constants are modifiable is described. The system has several important features, such as time constants for time-domain computations, interchangeable chips allowing a modifiable gross architecture, and expandability to any arbitrary size. Such an approach allows the exploration of different network architectures for a wide range of applications, in particular dynamic real-world computations. Four different modules (neuron, synapse, time constant, and switch units) have been designed and fabricated in a 2- mu m CMOS technology. About 100 of these modules have been assembled in a fully functional prototype neural computer. An integrated software package for setting the network configuration and characteristics, and monitoring the neuron outputs has been developed as well. The performance of the individual modules as well as the overall system response for several applications was tested successfully. Results of a network for real-time decomposition of acoustical patterns are discussed. >

Reconstitution de photochemically active reaction centers in planar phospholipid membranes: Light-induced electrical currents under voltage-clamped conditions

The initial light-activated electron transfer occurring within the photosynthetic bacterial reaction center protein (RC) of Rhodopseudomonas sphaeroides generates a charge separation and a redox potential difference between an oxidized cytochrome c and a reduced quinone. This is summarized in the scheme below in which ferri/ferrocytochrome c is the watersoluble cytochrome c2 that serves as an electron donor to the reaction center; (BChl)2 is a bacteriochlorophyll dimer. BPh is bacteriopheophytin, and Q1 and QU are the reaction center primary and secondary quinones, respectively. The times given are halftimes. See [ 1,2] for recent reviews of the reaction center photochemistry.

Acoustic-phonetic features for the automatic classification of stop consonants

In this paper, the acoustic-phonetic characteristics of the American English stop consonants are investigated. Features studied in the literature are evaluated for their information content and new features are proposed. A statistically guided, knowledge-based, acoustic-phonetic system for the automatic classification of stops, in speaker independent continuous speech, is proposed. The system uses a new auditory-based front-end processing and incorporates new algorithms for the extraction and manipulation of the acoustic-phonetic features that proved to be rich in their information content. Recognition experiments are performed using hard decision algorithms on stops extracted from the TIMIT database continuous speech of 60 speakers (not used in the design process) from seven different dialects of American English. An accuracy of 96% is obtained for voicing detection, 90% for place of articulation detection and 86% for the overall classification of stops.

Acoustic-phonetic features for the automatic classification of fricatives

In this article, the acoustic-phonetic characteristics of the American English fricative consonants are investigated from the automatic classification standpoint. The features studied in the literature are evaluated and new features are proposed. To test the value of the extracted features, a statistically guided, knowledge-based, acoustic-phonetic system for the automatic classification of fricatives in speaker-independent continuous speech is proposed. The system uses an auditory-based front-end processing system and incorporates new algorithms for the extraction and manipulation of the acoustic-phonetic features that proved to be rich in their information content. Classification experiments are performed using hard-decision algorithms on fricatives extracted from the TIMIT database continuous speech of 60 speakers (not used in the design/training process) from seven different dialects of American English. An accuracy of 93% is obtained for voicing detection, 91% for place of articulation detection, and 87% for the overall classification of fricatives.

An acoustic-phonetic feature-based system for automatic phoneme recognition in continuous speech

An acoustic-phonetic feature- and knowledge-based system for the automatic segmentation, broad categorization and fine phoneme recognition of continuous speech is described. The system uses an auditory-based front-end processing and incorporates new knowledge-based algorithms to automatically segment the speech into phoneme-like segments that are further categorized into 4 main categories: sonorants, stops, fricatives and silences. The final outputs from the system are 19 class phonemes which contain 7 stops, 6 fricatives, nasals and semivowels, 4 vowel classes and silences. The system was tested on continuous speech from 30 speakers having 7 different dialects from the TIMIT database which were not used in the design process. The results are 92% accuracy for the segmentation and categorization, 86% for the stop classification, 90% for the fricative classification, 75% for the nasal and semivowel extraction and 82% for the vowel recognition. These results compare favorably with previous phoneme classification results.

Spectrophotometric and voltage clamp characterization of monolayers of bacterial photosynthetic reaction centers

Abstract Bacterial photosynthetic reaction centers from Rhodopseudomonas sphaeroides have been spread on an air/aqueous interface, compressed, and transferred quantitatively to either glass or transparent, tin oxide-coated slides. These assemblies permit the concomitant measurement of both optical and electrical activities to be made on protein films under voltage-clamp conditions. Optical spectra of the monolayer-coated slides reveal characteristic reaction center absorptions. Linear dichroism spectra of the monolayers indicate that the reaction center is aligned on the air/aqueous interface with an angle of inclination which is essentially the same as it is with respect to the membrane plane in vivo. The kinetics of the light-induced absorbance changes of the reaction center in the deposited films are essentially unaltered from those in solution; however, there is some loss in the extent of photochemical activity. Measurement of the light-induced electrical transients shows capacitative charging and discharging currents, which can be readily associated with the reaction center bacteriochlorophyll dimer to ubiquinone electron transfer. The extent of the photochemical activity detected by the voltage-clamp is at best only 10–12% of that measured by optical assay. This suggests that on the air/aqueous interface, the reaction centers must be predominately oriented with opposing directions of electron transfer, having only a slight, variable tendency to align with the ubiquinone directed toward the aqueous phase. In spite of the present shortcomings, these assemblies appear to be uniquely useful to study the effect of clamped potentials on the kinetics and mechanisms of electron transfer.

Non-parallel training for voice conversion by maximum likelihood constrained adaptation

The objective of voice conversion methods is to modify the speech characteristics of a particular speaker in such manner, as to sound like speech by a different target speaker. Current voice conversion algorithms are based on deriving a conversion function by estimating its parameters through a corpus that contains the same utterances spoken by both speakers. Such a corpus, usually referred to as a parallel corpus, has the disadvantage that many times it is difficult or even impossible to collect. Here, we propose a voice conversion method that does not require a parallel corpus for training, i.e. the spoken utterances by the two speakers need not be the same, by employing speaker adaptation techniques to adapt to a particular pair of source and target speakers, the derived conversion parameters from a different pair of speakers. We show that adaptation reduces the error obtained when simply applying the conversion parameters of one pair of speakers to another by a factor that can reach 30% in many cases, and with performance comparable with the ideal case when a parallel corpus is available.

A new temporal domain optical flow measurement technique for focal plane VLSI implementation

A new temporal domain technique for optical flow measurement is presented. This approach, which has been developed primarily for VLSI implementation, requires only the sign of spatiotemporal derivatives, 1-b Boolean multiplication and integer arithmetic to compute image velocity. Hence, it can be easily and efficiently implemented in hardware and software. It is composed of a hybrid of the Reichardt and Ullman-Marr motion models and measures both speed and direction at every pixel. For image sequences, it measures the number of frames required for an edge to translate over a pixel, while in analog hardware, it measures the time. Direction is given by correlating the disappearance of an edge at one pixel with its reappearance at a neighboring pixel. A test chip of this scheme has been implemented in 2 /spl mu/m VLSI and was found to measure 2-D velocity over three orders of magnitude. A total of 0.1 mW of power was consumed per pixel in room light. Therefore, this technique offers simple, computationally efficient, and direct means for measuring wide spatiotemporal bandwidth image motion in both hardware and software.