Name
Title | ||
|---|---|---|
Spoken Language Understanding of Human-Machine Conversations for Language Learning Applications |
Abstract | ||
|---|---|---|
Spoken language understanding (SLU) in human machine conversational systems is the process of interpreting the semantic meaning conveyed by a user's spoken utterance. Traditional SLU approaches transform the word string transcribed by an automatic speech recognition (ASR) system into a semantic label that determines the machine's subsequent response. However, the robustness of SLU results can suffer in the context of a human-machine conversation-based language learning system due to the presence of ambient noise, heavily accented pronunciation, ungrammatical utterances, etc. To address these issues, this paper proposes an end-to-end (E2E) modeling approach for SLU and evaluates the semantic labeling performance of a bidirectional LSTM-RNN with input at three different levels: acoustic (filterbank features), phonetic (subphone posteriorgrams), and lexical (ASR hypotheses). Experimental results for spoken responses collected in a dialog application designed for English learners to practice job interviewing skills show that multi-level BLSTM-RNNs can utilize complementary information from the three different levels to improve the semantic labeling performance. An analysis of results on OOV utterances, which can be common in a conversation-based dialog system, also indicates that using subphone posteriorgrams outperforms ASR hypotheses and incorporating the lower-level features for semantic labeling can be advantageous to improving the final SLU performance. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s11265-019-01484-3 | JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY |
Keywords | DocType | Volume |
Spoken language understanding,Human-machine conversational systems,Computer assisted language learning,End-to-end modeling,Education | Journal | 92.0 |
Issue | ISSN | Citations |
SP8 | 1939-8018 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qian Yao | 1 | 527 | 51.55 |
| Rutuja Ubale | 2 | 2 | 3.17 |
| Patrick Lange | 3 | 9 | 8.42 |
| Keelan Evanini | 4 | 79 | 20.23 |
| Vikram Ramanarayanan | 5 | 70 | 13.97 |
| Frank K. Soong | 6 | 1395 | 268.29 |