دیزاینی Ender Turing Fonksiyona Nermalava Analîtîkî ya Navenda Bangan لەلایەن Lidiia Suslova خەڵاتگرێکی بەناوبانگی خەڵاتی شکۆمەندی 2023 Xelata A' Design Award a Tuncîn لە پۆلی پێشبڕکێی Dîzayna Navber, Danûstendin û Ezmûna Bikarhêner.
TuncNavber· 2023
Ender Turing Fonksiyona Nermalava Analîtîkî ya Navenda Bangan
لەلایەن Lidiia Suslova
کڕیار: Ender Turing
خەڵاتگری Xelata A' Design Award a Tuncîn لە پۆلی Navber
خەڵاتگری پشتڕاستکراو
پشتڕاستکردنەوەی باری خەڵات بۆ #149673دیزاینەکە
دەربارەی Ender Turing Fonksiyona Nermalava Analîtîkî ya Navenda Bangan
Ender Turing platformek nermalavî ya cloud-based e ku ji bo rêveberiya kalîteyê ya navendên bangan hatiye çêkirin. Panelek demjimêra rastîn (real-time dashboard) rê dide serpereşt û rêveberan ku performansê bi nûvekirinên zindî çavdêrî bikin. Pîvanên ku têne nîşandan ev in: hejmara bangan, navîna dema meşandinê, çareserkirina di bangê yekem de, xalên têrbûna xerîdaran û berdestiya nûnerên xizmetê. Pêş-nirxandina otomatîk a bangan û chatan dema vekolîna kalîteyê kurttir dike, û fîltreyên nerm dihêlin ku li şûna hemû axaftinan, tenê nimûneyek biçûk were hilbijartin. Scorecard (kartên nirxandinê) dikarin bêyî piştgiriya endezyariyê werin çêkirin û sererastkirin. Navrû (interface) bi zêdetirî deh zimanan tê pêşkêşkirin.
پێناسەکردن
دەربارەی Xelata A' Design Award a Tuncîn
Ender Turing Fonksiyona Nermalava Analîtîkî ya Navenda Bangan xelatgirê Xelata A' Design Award a Tuncîn e, nasîneke pir bi prestîj ku ji sêwiranên berbiçav ên bi afirînerî, jêhatîbûn û zîrekiyê têne cudakirin re tê dayîn. Xelatgirên Tuncînê karên bi têra xwe jêhatî û bi awayekî balkêş afirîner in, yên ku ezmûna fireh, xeyal û çareserkirina sêwiranerên xwe piştrast dikin. Tê hêvîkirin ku Ender Turing Fonksiyona Nermalava Analîtîkî ya Navenda Bangan tiştekî pir hatiye rêzgirtin, sitayişkirin û delal be, bi awayekî berbiçav pîşekar û nûjen. Ev sêwirana bi Tuncînê serketî pratîkên çêtirîn ên huner, zanist, sêwiran û teknolojiyê digire nav xwe û ji bo baldariya li hûrgiliyan hêja ye. Ender Turing Fonksiyona Nermalava Analîtîkî ya Navenda Bangan pêdiviyan bi rengekî xweş tîne cih, destê xwe dide daxwazan, hestan dihejîne û meraqê dikişîne.
لە پشت دیزاینەوە
کیتی چاپەمەنی
باوەڕپێکراوەکان، ئەندامانی تیم و وردەکاری تەکنیکی کە لەلایەن دیزاینەرەوە پێشکەش کراون.
- تایبەتمەندییە تایبەتەکان
- A real-time dashboard allows supervisors and managers to monitor call center KPIs and agent progress with live updates. It displays metrics such as call volume, average handle time, first call resolution, customer satisfaction scores, and agent availability. This helps identify areas of improvement, detect issues, and optimize call center performance through proactive management and data-driven decision-making, leading to improved efficiency, customer satisfaction, and business outcomes.
- قەبارە و پاکێج
- The primary function of Ender Turing engine is to help users create and train AI models that can understand and generate human-like language. The platform provides a range of NLP capabilities, including text classification, sentiment analysis, entity recognition, language translation, and text summarization, among others. Users can build custom models using Ender Turing's drag-and-drop interface or integrate pre-trained models into their applications using the platform's API.
- تاگەکان
- Artificial intelligence (AI), Natural language processing (NLP), Machine learning, Text classification, Sentiment analysis, Data processing, Text summarization API, Cloud-based platform, Language modeling, Text mining, Call center, Scoring
- تەکنەلۆژیای بەرهەمهێنان
- We used a data-driven design approach to gather feedback for our design, which involved observing and interviewing customers of the product. All of our decisions were based on identifying user pain points and areas of frustration. As a result, we developed a product solution that eliminates most pain points for call center supervisors, increases their productivity, reduces stress and frustration, and features an intuitive UX interface covered with more than 10 language options.
- هەڵەنگاندنی دیزاین
- Experiments were done to test hypotheses and validate design decisions. We found that our users are non-technical and prefer a more prominent communication style. We avoid using complex logic constructions and heavy interface decisions. Our UX solutions are continuously simplified.
- توێژینەوە
- As we maintain ongoing communication with our end users, including data center supervisors and stakeholders, we have collected data through a range of research methods, such as interviews, surveys, and observations.
This has allowed us to gain valuable insights into usesr needs, preferences, and behaviors, which will inform the design of effective solutions that meet their specific requirements. - ئیلهام
- Call centers handle up to 1000 calls per agent per day. Measuring and analyzing this data with metrics similar to those used by humans is crucial to improve client service and call center productivity. A productive call center saves businesses revenue and promotes polite and friendly communication with customers, enhancing a business's reputation, improving customer satisfaction, and increasing their overall quality of life.
- ماوەی پڕۆژە
- The project started in June 2020 in Tallinn, Estonia. The Design for the Project started at January 2022 and still developing and enhancing. Product was nominated as winner at Latitude59 pitching competition in May 2022, Tallinn, Estonia and took 2nd place at Infoshare Startup Contest where been selected among 500 startups from all over the world in October 2022, Gdansk, Poland.
- ڕێڕەوی کارکردن
- Our solution provides a 20-fold increase in speed for scoring calls and chats. This is made possible by automated AI pre-scoring and call center quality assurance. Using flexible filters, you can randomly select only a small number of calls and chats for quality monitoring, rather than monitoring all of them.
Moreover, our system allows for flexible setup of scorecards with no limitations. This means that you will no longer need engineers or Excel sheets to modify or create new scorecards. - پەتێنتەکان
- Scientific publications:
1. Transferability Evaluation of Speech Emotion Recognition Between Different Languages
January 2022
DOI:10.1007/978-3-031-04812-8_35
In book: Advances in Computer Science for Engineering and Education (pp.413-426)
Ievgen Iosifov
Olena Iosifova
Oleh Romanovskyi
Vladimir Sokolov
2. Automated Pipeline for Training Dataset Creation from Unlabeled Audios for Automatic Speech Recognition
July 2021
DOI:10.1007/978-3-030-80472-5_3
In book: Advances in Computer Science for Engineering and Education IV (pp.25-36)
Oleh Romanovskyi
Ievgen Iosifov
Olena Iosifova
Vladimir Sokolov
3. Analysis of Automatic Speech Recognition Methods
January 2021
Conference: Cybersecurity Providing in Information and Telecommunication SystemsAt: Kyiv, Ukraine
Olena Iosifova
Ievgen Iosifov
Vladimir Sokolov
Oleh Romanovskyi
Igor Sukaylo
4. Sentence Segmentation from Unformatted Text using Language Modeling and Sequence Labeling Approaches
October 2020
DOI:10.1109/PICST51311.2020.9468084
Conference: 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T)
Ievgen Iosifov
Olena Iosifova
Vladimir Sokolov
5. Methods and components of natural language processing
August 2020 Adaptive automatic control systems 1(36):93-113
DOI:10.20535/1560-8956.36.2020.209780
Olena Iosifova
Ievgen Iosifov
Oleksandr Rolik
6. Techniques Comparison for Natural Language Processing
June 2020
DOI:10.5281/zenodo.3895814
Conference: 2nd International Workshop on Modern Machine Learning Technologies and Data ScienceAt: Lviv-Shatsk, Ukraine
Olena Iosifova
Ievgen Iosifov
Oleksandr Rolik
Vladimir Sokolov
سپۆنسەرکراو
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