Spoken language is central to human communication and has significant links to both national identity and individual existence. The structure of spoken language is shaped by many factors. It is structured by the phonological, syntactic and prosodic structure of the language being spoken, by the acoustic enviroment and context in which it is produced---e.g., people speak differently in noisy or quiet environments---and the communication channel through which it travels.
Speech is produced differently by each speaker. Each utterance is produced by a unique vocal tract which assigns its own signature to the signal. Speakers of the same language have different dialects, accents and speaking rates. Their speech patterns are influenced by the physical environment, social context, the perceived social status of the participants, and their emotional and physical state.
Large amounts of annotated speech data are needed to model the affects of these different sources of variability on linguitic units such as phonemes, words, and sequences of words. An axiom of speech research is there are no data like more data. Annotated speech corpora are essential for progress in all areas of spoken language technology. Current recognition techniques require large amounts of training data to perform well on a given task. Speech synthesis systems require the study of large corpora to model natural intonation. Spoken languages systems require large corpora of human-machine conversations to model interactive dialogue.
In response to this need, there are major efforts underway worldwide to collect, annotate and distribute speech corpora in many languages. These corpora allow scientists to study, understand, and model the different sources of variability, and to develop, evaluate and compare speech technologies on a common basis.
Recent advances in speech and language recognition are due in part to the availability of large public domain speech corpora, which have enabled comparative system evaluation using shared testing protocols. The use of common corpora for developing and evaluating speech recognition algorithms is a fairly recent development. One of first corpora used for common evaluation, the TI-DIGITS corpus, recorded in 1984, has been (and still is) widely used as a test base for isolated and connected digit recognition
Challenges in spoken language corpora are many. One basic challenge is in design methodology---how to design compact corpora that can be used in a variety of applications; how to design comparable corpora in a variety of languages; how to select (or sample) speakers so as to have a representative population with regard to many factors including accent, dialect, and speaking style; how to create generic dialogue corpora so as to minimize the need for task or application specific data; how to select statistically representative test data for system evaluation. Another major challenge centers on developing standards for transcribing speech data at different levels and across languages: establishing symbol sets, alignment conventions, defining levels of transcription (acoustic, phonetic, phonemic, word and other levels), conventions for prosody and tone, conventions for quality control (such as having independent labelers transcribe the same speech data for reliability statistics). Quality control of the speech data is also an important issue that needs to be addressed, as well as methods for dissemination. While CDROM has become the defacto standard for dissemination of large corpora, other potential means need to also be considered, such as very high speed fiber optic networks
