Toward the ultimate synthesis/recognition system.

Abstract

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.VISION OF THE FUTURE For the majority of humankind, speech production and understanding are quite natural and unconsciously acquired processes performed quickly and effectively throughout our daily lives. By the year 2001, speech synthesis and recognition systems are expected to play important roles in advanced user-friendly human-machine interfaces (1). Speech recognition systems include not only those that recognize messages but also those that recognize the identity of the speaker. Services using these systems will include database access and management, various order-made services, dictation and editing, electronic secretarial assistance, robots (e.g., the computer HAL in 2001-A Space Odyssey), automatic interpreting (translating) telephony, security control, and aids for the handicapped (e.g., reading aids for the blind and speaking aids for the vocally handicapped) (2). Today, many people in developed countries are employed to sit at computer terminals wearing telephone headsets and transfer information from callers to computer systems (databases) and vice versa (information and transaction services). According to the basic idea that boring and repetitive tasks done by human beings should be taken over by machines, these information-transfer workers should be replaced by speech recognition and synthesis machines. Dictation or voice typewriting is expected to increase the speed of input to computers and to allow many operations to be carried out without hand or eye movements that distract attention from the task on the display. Fig. 1 shows a typical structure for task-specific voice control and dialogue systems. Although the speech recognizer, which converts spoken input into text, and the language analyzer, which extracts meaning from text, are separated into two boxes in the figure, ...

What is the Value of Embedding Artificial Emotional Prosody in Human–Computer Interactions? Implications for Theory and Design in Psychological Science

“…As computerized technology becomes an ever greater fixture at home and at work, our future interactions with it will need to become even more sophisticated ( Wendemuth and Biundo, 2011 ; Honold et al, 2014 ). Some time ago, it was recommended that artificial speech synthesis technology should not only have the ability to control prosody based on meaning, but also the capability to control individual speaking style (another form of prosody), choosing application-oriented speaking styles, and be able to add emotion ( Furui, 1995 ). Yet, as we have seen, there remains much work to be done ( Burkhardt and Stegmann, 2009 ).…”

“…Additional work on the social skills and responsivity with which HCI-AI are programmed will likely increase the empathy and acceptance level of interactions further ( Leite et al, 2013 ). From the human interface point of view, it has long been recognized that HCI-AI should be able to automatically acquire new knowledge about the thinking process of individual users, automatically correct user errors, and understand user intentions by accepting rough instructions and inferring details ( Furui, 1995 ). Ultimately, the hope for the future is that HCI-AI could extract the prosodic cues from a user’s speech, capitalize on the information to inform predictive models of likely emotions ( Litman and Forbes-Riley, 2006 ), and amend their own displays and actions accordingly.…”