Information Technology & Multimedia in English Language Teaching
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Evaluating five speech recognition programs for ESL learners
Hao-Jan Howard Chen
Foreign Language Division
Department of General Education
National Taiwan Ocean University
As personal computers become more powerful and affordable, they are becoming more attractive as tools for foreign language teaching/learning. More and more teachers and learners are increasingly interested in computer-assisted language learning (CALL) programs. Recently, many companies have incorporated speech recognition technology into their products which they claim can facilitate the development of listening and speaking skills. Although the programs featuring speech recognition technologies seem quite attractive, it is necessary to examine these programs more closely before they are adopted.
This paper uses a set of evaluation criteria based on second language acquisition (SLA) theory to examine the usefulness for learners of English as a Second Language (ESL) of five CD-ROM programs which use speech recognition technology.
Chapelle's Evaluation Criteria for Multimedia CD-ROMs
Teachers and learners lack clear evaluation guidelines and find it difficult to decide which programs in the wide range of multimedia CD-ROM titles available for English teaching and learning are useful. However, most existing evaluation guidelines are based on general educational theories or theories of computer-human interaction. Few take into account theories of second language acquisition or foreign language learning. To overcome this problem, Chapelle (1998) collected together, from other authors, a set of seven criteria for evaluating CD-ROM titles based on SLA interactionist theory. The criteria express conditions to be met by good programs. They are:
1. The linguistic characteristics of target language input need to be made salient (Doughty, 1991).
2. Learners should receive help in comprehending semantic and syntactic aspects of linguistic input (Larsen-Freeman & Long, 1991).
3. Learners need to have opportunities to produce target language output (Swain,1985).
4. Learners need to notice errors in their own output (Swain & Lapkin, 1995).
5. Learners need to correct their linguistic output (Swain, 1998).
6. Learners need to engage in target language interaction whose structure can be modified for negotiation of meaning (Long, 1996).
7. Learners should engage in L2 tasks (goal-oriented two-way communicative tasks) designed to maximize opportunities for good interaction (Pica, Kanagy, and Falodun, 1993).
According to Chapelle (1997, 1998, 1999) and Chen (1999), some of these conditions are met by many good CD-ROM titles. For instance, many programs highlight the key words or phrases in a lesson by using special fonts or colours. These programs are expected to provide enhanced input to language learners. In addition, CALL programs provide many different options for learners to achieve better comprehension. For instance, some programs provide simplified or annotated readings or listening materials recorded at a slower speed. Moreover, online references such as dictionaries or grammar notes are also provided.
Comprehensible output and corrective feedback are less well supported as many CALL programs can only elicit limited written output from learners (via multiple choice and blank-filling tests) and learners rarely have opportunities to write complete sentences. Because output opportunities are limited, corrective feedback only focuses on certain targeted linguistic items or structures. Most traditional CALL programs are unable to meet Chapelle's conditions 3, 6 and 7.
Speech recognition technology may improve the ability of CALL software to provide corrective feedback thus creating beneficial language learning conditions. This paper examines five commercial software packages featuring speech recognition technologies in order to compare facilities offered and find examples of the best practices. The programs are briefly introduced, their speech recognition capacities are examined and their strengths and limitations in helping ESL/EFL learners develop better speaking skills are discussed.
Five CD-ROM programs featuring speech recognition technology
The five pieces of software compared in this paper are: Caroline in the City/CNN Interactive English (Hebron Soft), Syracuse English Comprehensive Learning Series (Syracuse Language), TeLL Me More Pro (Auralog), TRACI Talk (CPI), and Encarta Interactive English Learning (Microsoft).
Caroline in the City / CNN Interactive English
Caroline in the City was created specifically for Chinese learners of English. The content is taken from a very popular CBS TV comedy show called Caroline in the City. The program focuses mainly on developing listening and speaking skills. It combines full screen video and a wide range of powerful learning tools. Learners can manipulate the video extensively and can request monolingual or bilingual subtitles at any time. They can view the complete program scripts or practise any word/phrase used in the show by using the comprehensive glossary. Grammar notes and quizzes are also available.
Speech recognition technology is used in role-play activities (Figure 1) where learners choose a role from the show. They read their dialogue (shown on the screen) to the computer which uses the Microsoft Speech Recognition Engine to evaluate their output and give them feedback. Learners can try again, skip a sentence, or ask for modelling when the recogniser does not accept their output.
The settings of the speech recognition engine in this program can be misleading. Although learners can adjust the sensitivity of the speech recognition engine, if it is adjusted too high, few sentences will be accepted and if adjusted too low all sentences will be accepted. The program does not specify clearly what level is suitable for learners which could lead to a distressing learning experience.
Figure 1: The role-play activities in Caroline in the City
The successor to Caroline in the City, CNN Interactive English is similar although it allows learners to record their voice and compare it with a native speaker using an on-screen voice (Figure 2). However, it is doubtful whether second language learners can really improve their pronunciation and intonation by examining the speech spectrum. As indicated by Ehsani & Knodt (1998), researchers have not yet provided clear experimental evidence for the effectiveness of this type of visual feedback. They suggest it should be presented with other types of feedback and with instructions on how to interpret the displays.
Figure 2: The voice spectrum in CNN Interactive English
Syracuse English Comprehensive Learning Series
The Syracuse English Comprehensive Learning Series (Syracuse Language) has 7 levels but we will concentrate here on levels 4 to 7 which focus on developing the four language skills with college level students. The key learning activities and tools include: video role play (using the IBM Speech Recognition Engine), interactive conversations, listening comprehension, reading and writing, vocabulary, grammar, cultural notes, record/playback, and an English dictionary.
In the role-play activities (Figure 3), learners first watch a video of a conversation and then play a role in the conversation. They then record their lines of the conversation during which the speech recognition engine evaluates the quality of their pronunciation and intonation. If unacceptable, they are asked to try again. During experimentation the speech recogniser proved mostly reliable by accurately distinguishing between the clear and unclear utterances of ESL learners.
Figure 3: The role play activity in the English Comprehensive Learning Series
Another activity engages learners in a dialogue. After listening to an electronic conversation partner, learners choose an appropriate response from three on-screen options which they read aloud to the microphone. Acceptable answers cause the conversation partner to smile and continue the conversation. Unacceptable answers cause a puzzled face and repetition (Figure 4).
Figure 4: A response to an inappropriate answer
TeLL Me More Pro
In TeLL Me More Pro each lesson follows the same format. Lessons are based on video scenes and include an interactive dialogue, a pronunciation practice, a comprehension activity and a range of additional exercises which support vocabulary and grammar structure acquisition.
In the dialogue mode of this program, learners first listen to the program then choose one of three acceptable responses given on screen and pronounce it clearly into the microphone (Figure 5). TeLL Me More acknowledges the response by highlighting it. The dialogue develops according to the responses learners choose. If a response is not understood, learners must try again. Like Caroline in the City, learners can adjust the sensitivity of the speech recogniser. The accuracy of speech recognition in this program proved quite reliable in testing.
Figure 5: A conversation with TeLL Me More Pro
In the pronunciation practice, learners listen to a selected word or sentence and then try to reproduce it. The program scores the attempt by matching user input with the model (Figure 6). Voice graphs and pronunciation scores are quite elaborate but no help is provided to interpret. This is the kind of visual feedback that Ehsani and Knodt (1998) suggest should be accompanied by other types of feedback and for which learners need help in interpreting the displays. The educational value of this activity would be significantly enhanced if learners could understand the meaning of the voice graph or why their utterances do not match the model.
Figure 6: Pronunciation practice in TeLL Me More Pro
Perhaps the most well-known ESL CD-ROM program featuring speech recognition technology is TRACI Talk. TRACI is an acronym for Teacher Ranging Across the Computer Interface which represents the concept of a teacher within the computer who is available to help the user whenever needed. TRACI Talk uses IBM VoiceType speech recognition and allows virtually hands-free interaction with the computer. It is a highly interactive ESL/EFL program.
TRACI Talk allows learners to engage in a series of task-based conversations with characters in the computer. Playing the role of detective, learners obtain information from four suspects to solve an interesting and challenging mystery. Learners take their turns in conversations by selecting and reading into a microphone one of three utterances shown on the screen (Figure 7). Learners have opportunities for extended conversations with the characters that can take many paths. This exposes them to a large amount of natural and communicative English.
Figure 7: The options of response shown on TRACI Talk screens
As in real conversations, learners may ask for sentences to be repeated or rephrased, and they need to steer the conversation to find out the answers to their questions. The desire to solve the mystery motivates learners to listen carefully, speak clearly and keep asking questions. Also learners may repeat entire conversations during which they can obtain additional information by following different paths. When learners feel they know enough about the characters, they can go to the next level by answering eight questions correctly (taken randomly from a pool of 60). If they pass this test, they can invite the suspects to their place for a chat and try to solve the mystery. If they do not pass the test, they can go back to previous sections looking for more information or they can try to answer another set of questions.
When tested on a range of computers, TRACI Talk's speech recognition engine performed moderately well. The program processed oral input quickly and provided smooth interaction. However, when input is inadequate, the program always responds with "Sorry, I do not catch that, could you say again." or similar sentences. The feedback did not indicate what was wrong with the input, not even making a distinction between pronunciation or intonation errors. Thus learners cannot learn how to correct their mistakes. If the feedback could pinpoint learners' weaknesses, the learning experience would be more useful and pleasant.
Encarta Interactive English Learning
Encarta Interactive English Learning mixes several multimedia technologies such as video, real-time 3D animations and speech recognition to immerse users in English. On first starting the software, users create a profile which tracks their progress. Encarta Interactive English Learning offers more than 360 different activities grouped into 10 units. Every unit contains listening, speaking, practice and vocabulary learning activities, each of which offers learners a choice of exercise types. When a unit has been completed learners take a Virtual Challenge which tests them on the main elements of the unit.
Speech recognition technology is used in the speaking activities and the virtual challenges. In the speaking activities, learners play a role in a video segment. They record their own voices after listening to a native speaker model (Figure 8) but the program does not provide any feedback making it impossible for learners to know how well they have performed.
Figure 8: Recording voice in the speaking activity of Encarta Interactive English
The Virtual Challenge provides a 3D virtual environment in which learners move around in a virtual space and interact with the characters (Figure 9) who either question the learners or provide them with useful information. Learners are also submitted to the same problems or difficulties the characters encounter. This experience is intended to increase interactivity and bring users into contact with the English language. The tasks (answering questions, looking for other characters and talking with them, and finding objects and bringing them back to specific locations) are challenging and fun. Navigation is easy so learners will feel they are actually walking and talking in this virtual environment. This is a motivating language learning environment.
Figure 9: The virtual challenge in Encarta Interactive English Learning
The performance and the judgement of the speech recognition engine in Encarta Interactive English Learning are not impressive. In some cases any learner input is accepted although in others the speech recogniser does have clear targets to match. However, when irrelevant or improper utterances are made more than two or three times the program automatically re-shows the relevant video segments (Figure 10). This clever intervention allows learners to recall what they have learned earlier. The Virtual Challenge sessions in Encarta Interactive English Learning require learners to produce language with no on-screen prompts. This is challenging for the learners and also for the speech recogniser because it has to be able to recognise a wide range of possible answers. This requirement might sometimes reduce the accuracy rate of the speech recogniser.
Figure 10: The intervention during an interaction in the Virtual Challenge
Ehsani and Knodt (1998) identify two fundamentally different system design types for speech recognition: closed response and open response. In closed response systems such as Tell Me More and TRACI Talk, learners must choose one response from a limited number of possible responses presented on the screen. Learners know exactly what they are allowed to say in response to any given prompt. By contrast, in open response systems like Encarta Interactive English Learning, the possible responses remain hidden and the learner is challenged to generate the appropriate response without any cues from the system. The accuracy rate of open response systems is not as high as that of closed response systems.
Kenworthy (1987) and Eskenazi (1999) propose five basic principles that contribute to success in computer-assisted pronunciation training situations.
1. Learners must produce large quantities of sentences on their own.
2. Learners must receive pertinent corrective feedback.
3. Learners must hear many different native models.
4. Prosody (amplitude, duration, and pitch) must be emphasized.
5. Learners should feel at ease in the language learning situation.
These principles can also be applied to assess the quality of the commercial programs reviewed here.
Although all of the programs encourage learners to speak up and produce more comprehensible output (Chapelle's third condition), most of them do not satisfy the first principle because they do not require learners to generate their own sentences. This is because speech recognisers work better in closed response designs (Ehsani & Knodt, 1998) which restrict learners to passive roles like reading aloud from written choices (Berstein, 1994; Eskenazi, 1999). Under these systems learners have no practice in constructing utterances on their own which is a major problem identified by a number of researchers (cf. Eskenazi, 1999). However, such systems do allow learners to practise example sentences. Under open response systems, learners can generate their own expressions but the recogniser might not be able to rule out incorrect answers.
The second principle is also not fully met because the quality of feedback varies. Encarta's Conversation activity gives no feedback. Language Connect and TeLL Me More only allow learners to continue their conversations if their contributions are acceptable. Users of the Virtual Challenge in Encarta Interactive English Learning can assess their own performance by checking if they have successfully completed the assigned tasks. The explicit feedback given by TRACI Talk is unfocused. However, there is also implicit feedback provided by the user's ability to meet the challenge of obtaining essential information by interacting with characters in the story. Most of the time, the programs deal with unclear utterances by simply asking learners to repeat without indicating the cause of the problem. More accurate feedback is needed for CALL because it will prevent learners becoming frustrated or confused, and will assist them in improving their oral English. The software reviewed here still needs to improve in this regard.
The third principle is generally met by these programs; they all provide a range of native speaker models for learners to imitate. The fourth principle requires an emphasis on prosody. While some of these programs offer spectrum as a visual feedback, the component is not explicitly emphasized in most programs. To satisfy the fifth principle programs should make learners feel at ease. A survey conducted at National Taiwan Ocean University with students who had used TRACI Talk for more than seven weeks indicated that talking to a machine reduced their anxieties in speaking a foreign language. They also found the program intelligent and non-threatening. It seems likely that users of other software would also feel at ease.
Clearly, the five commercial programs reviewed here can not provide all of the ideal learning conditions recommended by Carol Chapelle (1998). The main problem is that to allow learners to freely negotiate with computers is a daunting task for software programmers because, as Chapelle (1998) points out, to engage in such a goal-oriented conversation with natural language the program "would require more than language recognition at the word and sentence level. It would require a 'knowledge base' about the courses, schedules, and advising routines" (p.28).
Although these commercial products are far from perfect, they can facilitate second language development. Their main advantages are that they: push learners to practise and/or produce large quantities of sentences (either those provided by the CALL programs or their own expressions); provide some pertinent corrective feedback; offer different native models; and create a less threatening environment for developing speaking skills. The potential of well-designed CALL programs which incorporate speech recognition technology should not be underestimated by any language teacher.
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