• No results found

Speech Emotion Recognition Using Convolutional Recurrent Neural Networks with Attention Model

N/A
N/A
Protected

Academic year: 2020

Share "Speech Emotion Recognition Using Convolutional Recurrent Neural Networks with Attention Model"

Copied!
10
0
0

Loading.... (view fulltext now)

Full text

Loading

Figure

Figure 1. Utterance distribution about four emotions.
Figure 3. The convolutional architecture for one mid-term segment.
Figure 7. An angry utterance with VAD.

References

Related documents

Of the 291 unique comment letters pertaining to Medicaid Section 1115 waiver applications in five states, 186 (64 percent) were submitted by citizens, of which 55 identified

Sessions including audio (VoIP), multipoint video, and all web conferencing features – PowerPoint, document, browser, application, region and complete desktop sharing – can be

The ODR process could then follow in accordance with the parties’ previous agreement (per- haps mediation, arbitration, or crowdsourced resolutions). Depending on the out-

The concepts of 'nation,' 'nationalism,' 'nationalization,' 'millet,' 'ulus,' 'national identity' and alike will be taken under theoretical investigation and their

This study reveals that, given a half-hour increase in the minimum nursing hours per resident day for licensed nurses, quality of patient care increases by 25 percent.. This

All food contact surfaces, equipment, and utensils used for the preparation, packaging, or handling of any cottage food products shall be washed, rinsed, and

Figure 5 considers the case of a hedge fund with short iShare positions of up to 100%. The average optimal asset allocation changes dramatically once again. As

In May 2013, the Standing Council on Tertiary Education, Skills and Employment (SCOTESE) and the Standing Council on Schools Education and Early Childhood (SCSEEC) established a