Chatbots and Automated Speech Recognition
(ASR) in EFL/ESL Classroom
The ability to understand human language;
to ask a question and to receive an answer, to generate realistic and
logically consistent responses are the core of human communication. Moreover,
with the rapid progression of technology, speech understanding technologies; chatbots and automated speech recognition (ASR) progressed as well, and now a range of speech
understanding applications are
available to language learners and teachers. Furthermore, These
applications enable EFL/ESL teachers and learners
to address a variety of learning issues. In other words, the successful implementations of these technologies give the learners the chance to improve
their speaking skills. Namely, speech understanding technologies give the learners
the opportunity to interact with a ‘speaker’ of English whenever they choose. For
instance, automated speech recognition
(ASR) can be implemented in the teaching
and learning process (A2-B2, 12+, a variety
of topics) as a useful pedagogical tool to
boost meaning-focused speaking interaction. In other words, it gives the learners the opportunity to have meaningful face-to-face discussions with the virtual interlocutor. An additional value of ASR is in their
versatility to address a variety of learning issues and topics. Namely, ASR is
a way for students to improve their pronunciation, gain awareness of their
articulation and boost their speaking
skills.
However,
ASR has also limitations, which should be taken into consideration. The
straightforward process of speech recognition by the machine is a complicated
process by variability issues. One issue is
connected with the peaks and troughs of the speech signal, that may not line up correctly when words are said
at a slower or faster rate. Moreover, the variability among speakers is
another problem: voice quality, an accent
that all affect speech characteristics.
Furthermore, unlike printed text, spoken language does not have clear-cut
boundaries between words. Therefore, sounds at the beginnings and ends of words
could be produced slightly differently depending on their immediate context.
While there is still another way to provide language learners with
conversation practice machine:
'chatbot'. The linguistic worth of ‘chatbot’ software programs is to hold a
conversation or interact, as a precursor to their potential as an ESL learning resource. Thus, Chatbots can be implemented in the
teaching and learning process, as a
suitable pairing of pedagogy and technology, if the following aspects are taken into consideration:
Chatbots work well when the language input to
them consists of one-clause sentences and when the topic is an everyday one. It is noteworthy that chatbots which perform
better converse in a single domain and have specialised vocabularies and
discussion topics (A2-B2, 12+, vocabulary: single domain).
Moreover, Chatbots need correctly-spelt words in grammatically correct
sentences. Some chatbots can deal with misspellings, but this is often
unpredictable, as the ability of chatbots to maintain a cohesive
exchange over multiple conversations is
limited. Thus, these limitations are
non-trivial and cannot be overlooked.
However, for practical purposes, the virtual dialogue can avoid the problems of
speech synthesis and lack of conversational cohesion, and in this case, it remains
a worthwhile option for CALL application.
