Aifanfan IM ናይ ዓማዊል ኣገልግሎት መተግበሪ by Baidu Online Network Technology Beijing is a highly esteemed winner of the very prestigious 2023 ናይ ሓጺን ሽልማት A' Design Award in ንድፊ ቴክኖሎጂ ሓበሬታ Competition Category.
ሓጺንቴክኖሎጂ ሓበሬታ· 2023
Aifanfan IM ናይ ዓማዊል ኣገልግሎት መተግበሪ
by Baidu Online Network Technology Beijing
Client: Baidu Online Network Technology. Beijing
ናይ ሓጺን ሽልማት A' Design Award Winner in ቴክኖሎጂ ሓበሬታ Category
Verified Award Winner
Verify Award Status for #144072The Design
About Aifanfan IM ናይ ዓማዊል ኣገልግሎት መተግበሪ
ኣይፋንፋን IM ንኦንላይን ድሕሪ-ሽያጭ ደገፍ ዝኸውን ብልሂ ናይ ዓማዊል ኣገልግሎት መተግበሪ እዩ። እዚ መተግበሪ ካብ ናይ ኣገልግሎት ወከልቲን ተጠቀምትን ዘሎ ክልተ-ኣንፈታዊ ርክብ ንምቕላል፡ ደገፍ ንኣታዊ (input assistance)፡ ምምሕያሽ ሂደት፡ ከምኡውን ናይ ሰብ ሰራሽ ብልሂ (AI) ሓጋዚ ይህብ። ካልእ ንጻል (multi modal) ኣታዊ፡ ካሜራን ድምጽን ዝሓቖፈ፡ ወጻእተኛ ቋንቋታትን ኣዘራርባታትን ንምልላይ ብምጥቃም ናይ ኣታዊ መደረኽ (threshold) ይንኪ። እቲ ናይ AI ሓጋዚ ኣብ ናይ ዝርርብ ጽሑፍ ዘለው ስምዒታዊ ረቛሒታት ብህሞት ይትንትን፡ ከምኡውን ቅልጡፍ ናይ መልሲ ትሕዝቶ ይመክር። ናይ ድምጺ ምልላይ፡ ናይ ስእሊ ምልላይ፡ ከምኡውን ተፈጥሮኣዊ ቋንቋ መስርሒ (NLP) ጥቕሚ ይግበረሎም።
The Recognition
About the ናይ ሓጺን ሽልማት A' Design Award
Aifanfan IM ናይ ዓማዊል ኣገልግሎት መተግበሪ ናይ ሓጺን ሽልማት A' Design Award ዝዓወተ እዩ፣ ካብ ጽቡቕ ዝተዳለዉ ፍጥረታት ዝጽበዩ ሞያውን ኢንዱስትሪኣውን ጠለባት ንዝመላኡ ጽቡቓት ዲዛይናት ዝወሃብ ክቡር ኣፍልጦ። ዘዓወቱ ሓጺን ዓቢ ክእለት፣ ልዑል ፍሉይነት፣ ክኢላዊ ርድኢትን ፈጠራዊ ዓቕምን ፈጣርዮም የርእዩ። Aifanfan IM ናይ ዓማዊል ኣገልግሎት መተግበሪ ብብዙሕ ዝተመነየ፣ ዝደነቐን ዝፈተዎን፣ ተግባራውን ሓድሽን ፍጥረት ክኾን ይጽበ። እዚ ዝዓወተ ዲዛይን ናይ ሓጺን ሽልማት A' Design Award ንዝበለጹ ልምድታት ኢንዱስትሪ የጣምር፣ ምስ ፍልጠትን ተውህቦን ዝተኣሳሰሩ ብቑዓት ቴክኒካውያን ባህርያት ድማ ኣለዎ። Aifanfan IM ናይ ዓማዊል ኣገልግሎት መተግበሪ ብጥንቃቐኡ ይኽበር፣ ንዓለም ዝሓሸ ቦታ ክትኸውን ዝሕግዙ ምምሕያሻት መዓርግ ህይወት ንምቕራብ ድማ ዝተዳለወ እዩ።
Behind the Design
Press Kit
Credits, team members and technical details provided by the designer.
- Unique Properties
- A smart customer service system with a series of optimization tools for customer service and consumers, such as input assistance, process optimization, and AI assistant, aiming to simplify the two-way communication process of both ends, provides more reliable security and protection, and supports multi-device and multi-scenario input switching, making the communication process easier and more convenient.
- Tags
- Customer service system, Program, Online customer service, After-sales service, AI technology
- Production Technology
- It uses the leading AI technologies of Baidu, such as speech recognition, image recognition, and natural language processing.
- Design Challenge
- The challenge in this project research is to optimize the two-end process. In the design process, it is necessary to balance the two-way needs of customer service and users, so that the process optimization of one end does not impose burden on the other. Therefore, the application is developed based on the pain points of users and customer service through various investigation methods.
- Research
- The application is developed through conducting questionnaire survey by the design team based on a multi software customer service system, collecting objective problems with the current intelligent customer service system, and analyzing user sentiment, usage scenarios and current design trends.
- Inspiration
- As online service platforms develop, the growth of online customer service has been achieved. However, due to the digitalization, many users who are not familiar with smart devices face problems in online communication, making it hard to obtain good after sales service. The complex flow of data and information and text descriptions cause problems to customer service. The application aims to meet the needs of both ends, lower the threshold, and improve service efficiency and user satisfaction.
- Project Duration
- The project was designed and developed in Beijing in April 2021 and went live in China in October 2021
- Operation Flow
- Multi modal input methods, including camera and voice input, can recognize foreign languages and dialects to lower the input threshold. Users can search for corresponding keywords or key words through communication aids to better understand the meaning of sentences while talking. The equipped AI assistant can analyze the emotional factors in the dialogue text in real time, generate response statements, and recommend quick response content to users.
- Team Members
- Yuan Lu
Fengyang Wang
Yujie Shi
Yi Liao
Nuo Xu
Liying Li
Li Liu
Xue Luan
Tian Xie
Lu Gan
Yanyan Wei
Jingjing Luo
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