Views provided by UsageCounts
This Dataset is associated with the paper "Syllable-Rate-Adjusted-Modulation (SRAM) Predicts Clear and Conversational Speech Intelligibility". It contains 144 sentences recorded from two talkers (one female, one male) in both clear and conversational styles (72 sentences in each style). The sample rate was 16000Hz. The silence periods before and after the speech were removed. The speech scripts for each speech style and the human performance are included in each sub-folder. SSN.wav is the steady-state noise used to create the noisy speeches. File Structure: - Female - Clear - 1.wav - ... - 72.wav - Convo - 1.wav - ... - 72.wav - human_results.csv - key_words_clear.txt - key_words_conv.txt - Male - SSN.wav
{"references": ["Liu, Sheng, Elsa Del Rio, Ann R. Bradlow, and Fan-Gang Zeng. 2004. \"Clear Speech Perception in Acoustic and Electric Hearing.\" The Journal of the Acoustical Society of America 116 (4): 2374\u201383. https://doi.org/10.1121/1.1787528."]}
Clear Speech, Conversational Speech
Clear Speech, Conversational Speech
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 4 |

Views provided by UsageCounts