The role of voice input for human-machine communication.

Optimism is growing that the near future will witness rapid growth in human-computer interaction using voice. System prototypes have recently been built that demonstrate speaker-independent real-time speech recognition, and understanding of naturally spoken utterances with vocabularies of 1000 to 2000 words, and larger. Already, computer manufacturers are building speech recognition subsystems into their new product lines. However, before this technology can be broadly useful, a substantial knowledge base is needed about human spoken language and performance during computer-based spoken interaction. This paper reviews application areas in which spoken interaction can play a significant role, assesses potential benefits of spoken interaction with machines, and compares voice with other modalities of human-computer interaction. It also discusses information that will be needed to build a firm empirical foundation for the design of future spoken and multimodal interfaces. Finally, it argues for a more systematic and scientific approach to investigating spoken input and performance with future language technology.

A test of the "jigsaw puzzle" model for protein folding by multiple methionine substitutions within the core of T4 lysozyme.

To test whether the structure of a protein is determined in a manner akin to the assembly of a jigsaw puzzle, up to 10 adjacent residues within the core of T4 lysozyme were replaced by methionine. Such variants are active and fold cooperatively with progressively reduced stability. The structure of a seven-methionine variant has been shown, crystallographically, to be similar to wild type and to maintain a well ordered core. The interaction between the core residues is, therefore, not strictly comparable with the precise spatial complementarity of the pieces of a jigsaw puzzle. Rather, a certain amount of give and take in forming the core structure is permitted. A simplified hydrophobic core sequence, imposed without genetic selection or computer-based design, is sufficient to retain native properties in a globular protein.

Toward the ultimate synthesis/recognition system.

This paper predicts speech synthesis, speech recognition, and speaker recognition technology for the year 2001, and it describes the most important research problems to be solved in order to arrive at these ultimate synthesis and recognition systems. The problems for speech synthesis include natural and intelligible voice production, prosody control based on meaning, capability of controlling synthesized voice quality and choosing individual speaking style, multilingual and multidialectal synthesis, choice of application-oriented speaking styles, capability of adding emotion, and synthesis from concepts. The problems for speech recognition include robust recognition against speech variations, adaptation/normalization to variations due to environmental conditions and speakers, automatic knowledge acquisition for acoustic and linguistic modeling, spontaneous speech recognition, naturalness and ease of human-machine interaction, and recognition of emotion. The problems for speaker recognition are similar to those for speech recognition. The research topics related to all these techniques include the use of articulatory and perceptual constraints and evaluation methods for measuring the quality of technology and systems.

The design, computer modeling, solution structure, and biological evaluation of synthetic analogs of bryostatin 1

The bryostatins are a unique family of emerging cancer chemotherapeutic candidates isolated from marine bryozoa. Although the biochemical basis for their therapeutic activity is not known, these macrolactones exhibit high affinities for protein kinase C (PKC) isozymes, compete for the phorbol ester binding site on PKC, and stimulate kinase activity in vitro and in vivo. Unlike the phorbol esters, they are not first-stage tumor promoters. The design, computer modeling, NMR solution structure, PKC binding, and functional assays of a unique class of synthetic bryostatin analogs are described. These analogs (7b, 7c, and 8) retain the putative recognition domain of the bryostatins but are simplified through deletions and modifications in the C4-C14 spacer domain. Computer modeling of an analog prototype (7a) indicates that it exists preferentially in two distinct conformational classes, one in close agreement with the crystal structure of bryostatin 1. The solution structure of synthetic analog 7c was determined by NMR spectroscopy and found to be very similar to the previously reported structures of bryostatins 1 and 10. Analogs 7b, 7c, and 8 bound strongly to PKC isozymes with Ki = 297, 3.4, and 8.3 nM, respectively. Control 7d, like the corresponding bryostatin derivative, exhibited weak PKC affinity, as did the derivative, 9, lacking the spacer domain. Like bryostatin, acetal 7c exhibited significant levels of in vitro growth inhibitory activity (1.8–170 ng/ml) against several human cancer cell lines, providing an important step toward the development of simplified, synthetically accessible analogs of the bryostatins.

Peptide design by artificial neural networks and computer-based evolutionary search

A technique for systematic peptide variation by a combination of rational and evolutionary approaches is presented. The design scheme consists of five consecutive steps: (i) identification of a “seed peptide” with a desired activity, (ii) generation of variants selected from a physicochemical space around the seed peptide, (iii) synthesis and testing of this biased library, (iv) modeling of a quantitative sequence-activity relationship by an artificial neural network, and (v) de novo design by a computer-based evolutionary search in sequence space using the trained neural network as the fitness function. This strategy was successfully applied to the identification of novel peptides that fully prevent the positive chronotropic effect of anti-β1-adrenoreceptor autoantibodies from the serum of patients with dilated cardiomyopathy. The seed peptide, comprising 10 residues, was derived by epitope mapping from an extracellular loop of human β1-adrenoreceptor. A set of 90 peptides was synthesized and tested to provide training data for neural network development. De novo design revealed peptides with desired activities that do not match the seed peptide sequence. These results demonstrate that computer-based evolutionary searches can generate novel peptides with substantial biological activity.

Identification of receptor-binding domains on human interleukin 5 and design of an interleukin 5-derived receptor antagonist.

A detailed structure-function analysis of human interleukin 5 (hIL5) has been performed. The hIL5 receptor is composed of two different polypeptide chains, the alpha and beta subunits. The alpha subunit alone is sufficient for ligand binding, but association with the beta subunit leads to a 2- to 3-fold increase in binding affinity. The beta chain is shared with the receptors for IL3 and granulocyte/macrophage-colony-stimulating factor--hence the descriptor beta C (C for common). All hIL5 mutants were analyzed in a solid-phase binding assay for hIL5R alpha interaction and in a proliferation assay using IL5-dependent cell lines for receptor-complex activation. Most residues affecting binding to the receptor alpha subunit were clustered in a loop connecting beta-strand 1 and helix B (mutants H38A, K39A, and H41A), in beta-strand 2 (E89A and R91A; weaker effect for E90A) and close to the C terminus (T109A, E110A, W111S, and I112A). Mutations at one position, E13 (Glu13), caused a reduced activation of the hIL5 receptor complex. In the case of E13Q, only 0.05% bioactivity was detected on a hIL5-responsive subclone of the mouse promyelocytic cell line FDC-P1. Moreover, on hIL5-responsive TF1 cells, the same mutant was completely inactive and proved to have antagonistic properties. Interactions of this mutant with both receptor subunits were nevertheless indistinguishable from those of nonmutated hIL5 by crosslinking and Scatchard plot analysis of transfected COS-1 cells.