Du Xiaoman Financial Teams up with Chinese Academy of Sciences on Artificial Intelligence, Emotional Voice Recognition


Baidu’s fintech spinoff Du Xiaoman Financial has entered an agreement with the Chinese Academy of Sciences (CAS) to train up postdoc talent in the field of artificial intelligence (AI).

Du Xiaoman and the CAS Automation Research Institute held a ceremony on 15 September for the launch of the “Joint Postdoc Training Project” (联合培养博士后项目).

The Project has the purpose of “jointly recruiting and training postdoc talent in artificial intelligence and related fields,” as well as “training postdoc talent in the field of artificial intelligence with a focus on the primary tech R&D operations of both parties.”

Du Xiaoman CEO Zhu Guang (朱光) said that the key to driving the application of artificial intelligence to finance was having a cohort of “comprehensive talent” that possessed technological ability as well as understood finance.

“[We] hope to use the recruitment and training project in collaboration with CAS to jointly explore cutting-edge applications of artificial intelligence in the field of finance.”

The first undertaking of the collaborative initiative will be a project for the “Application of Emotion Detection Technology to Automated Voice Recognition” (情感识别技术在语音机器人).

Du Xiaoman said that its voice recognition technology already had an accuracy rate of over 95%, and that it had replaced 60% of repetitious work in lending operations.

The company’s voice recognition team claims to have upgraded its voice recognition technology within three days by using its big data and machine learning expertise, in order to help Chinese banks conduct remote operations during the COVID-19 pandemic.

“At present voice recognition technology is very capable when it comes to listening and understanding, but it still cannot comprehend emotions,” said Tao Jianhua (陶建华), a researcher from the CAS Automation Research Institute.

“We hope that the exploration of emotion computing can one day create a voice recognition technology that can not only understand what someone is saying, but can also determine whether an individual’s mood is happy or upset

“[This] will not only greatly improve customer experience and drive upgrades to smart customer systems throughout the financial sector, it also has major application value in multiple areas of social regulation.”

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