Avaya Conversational Intelligence: A Real-Time System for Spoken Language Understanding in Human-Human Call Center Conversations
September 02, 2019 Β· Declared Dead Β· π Interspeech
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jan Mizgajski, Adrian Szymczak, Robert GΕowski, Piotr SzymaΕski, Piotr Ε»elasko, Εukasz Augustyniak, MikoΕaj Morzy, Yishay Carmiel, Jeff Hodson, Εukasz WΓ³jciak, Daniel Smoczyk, Adam WrΓ³bel, Bartosz Borowik, Adam Artajew, Marcin Baran, Cezary Kwiatkowski, Marzena Ε»yΕa-Hoppe
arXiv ID
1909.02851
Category
eess.AS: Audio & Speech
Cross-listed
cs.CL,
cs.LG,
cs.SD,
stat.ML
Citations
2
Venue
Interspeech
Last Checked
3 months ago
Abstract
Avaya Conversational Intelligence(ACI) is an end-to-end, cloud-based solution for real-time Spoken Language Understanding for call centers. It combines large vocabulary, real-time speech recognition, transcript refinement, and entity and intent recognition in order to convert live audio into a rich, actionable stream of structured events. These events can be further leveraged with a business rules engine, thus serving as a foundation for real-time supervision and assistance applications. After the ingestion, calls are enriched with unsupervised keyword extraction, abstractive summarization, and business-defined attributes, enabling offline use cases, such as business intelligence, topic mining, full-text search, quality assurance, and agent training. ACI comes with a pretrained, configurable library of hundreds of intents and a robust intent training environment that allows for efficient, cost-effective creation and customization of customer-specific intents.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Audio & Speech
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
LPCNet: Improving Neural Speech Synthesis Through Linear Prediction
R.I.P.
π»
Ghosted
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking
R.I.P.
π»
Ghosted
TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech
R.I.P.
π»
Ghosted
Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders
R.I.P.
π»
Ghosted
Utterance-level Aggregation For Speaker Recognition In The Wild
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted