arXiv research

Algorithm recovers spike direction from modulo-reduced measurements in high dimensions.

Study identifies three quantization regimes for ReLU networks.

This paper introduces GLT for better input data representation in BNN and proposes a compact topology with block pruning.

Study examines cash conversion cycle in manufacturing firms, finding negative relationships with profitability and size.

Framework converts singer identity and vocal technique from non-parallel corpora.

FasterVoiceGrad speeds up VC by 6-7x with novel distillation.

Automated system extracts medication regimens from medical conversations.

Conversion prediction plays an important role in online advertising since Cost-Per-Action (CPA) has become one of the primary campaign performance objectives in the industry. Unlike click prediction, conversions have different types in nature, and each type may be associated with different decisive factors. In this pap…

FedConPE improves conversational recommender systems efficiency and privacy.

Contextual bandit algorithms provide principled online learning solutions to balance the exploitation-exploration trade-off in various applications such as recommender systems. However, the learning speed of the traditional contextual bandit algorithms is often slow due to the need for extensive exploration. This poses…

Study proposes a time-aware model to predict user conversion intent.

The goal of online display advertising is to entice users to "convert" (i.e., take a pre-defined action such as making a purchase) after clicking on the ad. An important measure of the value of an ad is the probability of conversion. The focus of this paper is the development of a computationally efficient, accurate, a…

CycleGAN-VC3 improves CycleGAN-VCs for mel-spectrogram conversion.

A new algorithm for conversational recommendation systems using dueling bandits in GLMs.

The paper extracts structured data from physician-patient conversations, reducing clerical burden.

Schedule-free SGD is optimal for nonconvex optimization problems.

Improved autoencoder for F0-consistent voice conversion.

Improved conversion rate prediction in online advertising using self-supervised pre-training.

A fast voice conversion method using diffusion models.

A method corrects feedback shift in predicting conversion rates with delayed feedback.

Proposes a new voice conversion model that preserves pitch patterns.

We present a voice conversion solution using recurrent sequence to sequence modeling for DNNs. Our solution takes advantage of recent advances in attention based modeling in the fields of Neural Machine Translation (NMT), Text-to-Speech (TTS) and Automatic Speech Recognition (ASR). The problem consists of converting be…

The paper provides a converse to linking theorems for graphs in 3-space and higher dimensions.

This paper proposes a voice conversion (VC) method using sequence-to-sequence (seq2seq or S2S) learning, which flexibly converts not only the voice characteristics but also the pitch contour and duration of input speech. The proposed method, called ConvS2S-VC, has three key features. First, it uses a model with a fully…

We address the problem of speech act recognition (SAR) in asynchronous conversations (forums, emails). Unlike synchronous conversations (e.g., meetings, phone), asynchronous domains lack large labeled datasets to train an effective SAR model. In this paper, we propose methods to effectively leverage abundant unlabeled …

This paper explores how LLMs can improve pipeline-based conversational agents.

A new framework converts EEG signals between subjects and tasks.

Unified approach for conversational recommendation by integrating attributes and items.

Neuro-symbolic system tackles conversational AI's need for natural, broad-ranging dialogue.

Estimates conversion probabilities from click sequences with privacy constraints.

Study finds neural dialog models struggle with conversational tasks.

Deep learning improves conversational recommender systems.

In this work we explored building automatic speech recognition models for transcribing doctor patient conversation. We collected a large scale dataset of clinical conversations ($14,000$ hr), designed the task to represent the real word scenario, and explored several alignment approaches to iteratively improve data qua…

In this paper we propose a multi-state model for the evaluation of the conversion option contract. The multi-state model is based on age-indexed semi-Markov chains that are able to reproduce many important aspects that influence the valuation of the option such as the duration problem, the time non-homogeneity and the …

Operator fields in the bundle of Dirac spinors and their conversion to spatial fields are considered. Some commutator equations are studied with the use of the conversion technique.

MathChat uses LLM agents to solve challenging math problems through conversational problem-solving.

Emerging resistive random-access memory (ReRAM) has recently been intensively investigated to accelerate the processing of deep neural networks (DNNs). Due to the in-situ computation capability, analog ReRAM crossbars yield significant throughput improvement and energy reduction compared to traditional digital methods.…

In this work we introduce a semi-supervised approach to the voice conversion problem, in which speech from a source speaker is converted into speech of a target speaker. The proposed method makes use of both parallel and non-parallel utterances from the source and target simultaneously during training. This approach ca…

This paper develops a new deep neural network optimized equalization framework for massive multiple input multiple output orthogonal frequency division multiplexing (MIMOOFDM) systems that employ low-resolution analog-to-digital converters (ADCs) at the base station (BS). The use of lowresolution ADCs could largely red…

SCM-GAN converts any song to sound like a different singer.

Innovative ball bearing converts rotary to reciprocating motion.

New method converts conventional ANNs to SNNs with minimal loss and efficiency.

Recent increases in basic food prices are severely impacting vulnerable populations worldwide. Proposed causes such as shortages of grain due to adverse weather, increasing meat consumption in China and India, conversion of corn to ethanol in the US, and investor speculation on commodity markets lead to widely differin…

This paper recovers smooth functions from noisy modulo samples using a three-stage strategy.

Let $h:X \to Y$ be a homeomorphism between hyperbolic surfaces with finite topology. If $h$ is homotopic to a holomorphic map, then every closed geodesic in $X$ is at least as long as the corresponding geodesic in $Y$, by the Schwarz Lemma. The converse holds trivially when $X$ and $Y$ are disks or annuli, and it holds…

Group discussions are essential for organizing every aspect of modern life, from faculty meetings to senate debates, from grant review panels to papal conclaves. While costly in terms of time and organization effort, group discussions are commonly seen as a way of reaching better decisions compared to solutions that do…

New algorithm speeds up user preference learning in conversational contexts.

End-to-end voice conversion without vocoder.