| P06-1004 | granularity are acceptable in spoken | lecture segmentation | . This is expected given the |
| N13-1096 | of the proposed RSI feature on | lecture segmentation | using an HMM . We represent each |
| P06-1004 | consider the task of unsupervised | lecture segmentation | . We formalize segmentation as |
| W06-1644 | resulting topic distributions to | lecture segmentation | . Acknowledgements We would like |
| P06-1004 | smoothing method developed for | lecture segmentation | may not be appropriate for short |
| P06-1004 | <title> Minimum Cut Model for Spoken | Lecture Segmentation | </title> Malioutov Barzilay Abstract |
| N13-1096 | underlying structure for better | lecture segmentation | and summarization . HMM has been |
| N13-1096 | which converts the audio to text , | lecture segmentation | which inserts paragraph boundaries |
| N13-1096 | lectures . 3 Incorporating RSI in | Lecture Segmentation | Several algorithms have been |
