124 citations · 127 across the 15 of their papers we have counts for
16 papers
Loud and Clear: Dynamic Activation Steering for Improving Speech Intelligibility in Noisy Environments
Seymanur Akti, Alexander Waibel
Speech becomes less intelligible in noisy environments, and humans naturally adapt their voice to compensate. Inspired by this behavior, we investigate whether a text-to-speech (TT…
Synthesizing the Lombard Effect: Multi-Level Control of Speech Clarity and Vocal Effort in TTS
Seymanur Akti, Alexander Waibel
Humans tend to speak louder and clearer in challenging environments, such as noisy conditions or when addressing hearingimpaired listeners, which is called Lombard effect. To simul…
KIT's Submission to Cross-Lingual Voice Cloning in IWSLT 2026
Seymanur Akti, Alexander Waibel
Cross-lingual voice cloning aims to generate speech in a target language while preserving speaker identity from a source-language reference. This task is central to speech translat…
Multilingual Long-Form Speech Instruction Following: KIT's Submission to IWSLT 2026
Enes Yavuz Ugan, Maike Züfle, Yuka Ko +5
With the advent of Large Language Models, single-task and token-based multi-task models have evolved into instruction-based systems that infer task and target language implicitly f…
Zero-Shot Lombard Speech Synthesis with Controllable Style Embeddings
Seymanur Akti, Alexander Waibel
The Lombard effect plays a key role in natural communication, particularly in noisy environments or when addressing hearing-impaired listeners. We present a controllable text-to-sp…
BOOM: Beyond Only One Modality KIT's Multimodal Multilingual Lecture Companion
Sai Koneru, Fabian Retkowski, Christian Huber +5
The globalization of education and rapid growth of online learning have made localizing educational content a critical challenge. Lecture materials are inherently multimodal, combi…
Shared Latent Representation for Joint Text-to-Audio-Visual Synthesis
Dogucan Yaman, Seymanur Akti, Fevziye Irem Eyiokur +1
We propose a text-to-talking-face synthesis framework leveraging latent speech representations from HierSpeech++. A Text-to-Vec module generates Wav2Vec2 embeddings from text, whic…
Streaming Non-Autoregressive Model for Accent Conversion and Pronunciation Improvement
Tuan-Nam Nguyen, Ngoc-Quan Pham, Seymanur Akti +1
We propose a first streaming accent conversion (AC) model that transforms non-native speech into a native-like accent while preserving speaker identity, prosody and improving pronu…
Towards Better Disentanglement in Non-Autoregressive Zero-Shot Expressive Voice Conversion
Seymanur Akti, Tuan Nam Nguyen, Alexander Waibel
Expressive voice conversion aims to transfer both speaker identity and expressive attributes from a target speech to a given source speech. In this work, we improve over a self-sup…
KIT's Offline Speech Translation and Instruction Following Submission for IWSLT 2025
Sai Koneru, Maike Züfle, Thai-Binh Nguyen +3
The scope of the International Workshop on Spoken Language Translation (IWSLT) has recently broadened beyond traditional Speech Translation (ST) to encompass a wider array of tasks…
Improving Pronunciation and Accent Conversion through Knowledge Distillation And Synthetic Ground-Truth from Native TTS
Tuan Nam Nguyen, Seymanur Akti, Ngoc Quan Pham +1
Previous approaches on accent conversion (AC) mainly aimed at making non-native speech sound more native while maintaining the original content and speaker identity. However, non-n…
Audio-Visual Speech Representation Expert for Enhanced Talking Face Video Generation and Evaluation
Dogucan Yaman, Fevziye Irem Eyiokur, Leonard Bärmann +3
In the task of talking face generation, the objective is to generate a face video with lips synchronized to the corresponding audio while preserving visual details and identity inf…
A Mobile Food Recognition System for Dietary Assessment
Şeymanur Aktı, Marwa Qaraqe, Hazım Kemal Ekenel
Food recognition is an important task for a variety of applications, including managing health conditions and assisting visually impaired people. Several food recognition studies h…
Fight Detection from Still Images in the Wild
Şeymanur Aktı, Ferda Ofli, Muhammad Imran +1
Detecting fights from still images shared on social media is an important task required to limit the distribution of violent scenes in order to prevent their negative effects. For…
A Comparative Study of Machine Learning Methods for Predicting the Evolution of Brain Connectivity from a Baseline Timepoint
Şeymanur Aktı, Doğay Kamar, Özgür Anıl Özlü +4
Predicting the evolution of the brain network, also called connectome, by foreseeing changes in the connectivity weights linking pairs of anatomical regions makes it possible to sp…
Vision-based Fight Detection from Surveillance Cameras
Şeymanur Aktı, Gözde Ayşe Tataroğlu, Hazım Kemal Ekenel
Vision-based action recognition is one of the most challenging research topics of computer vision and pattern recognition. A specific application of it, namely, detecting fights fr…