Christian Hildebrand

Course location

Home university

ESADE Barcelona
University of St.Gallen

Course location

ESADE Barcelona

Home university

University of St.Gallen
Christian Hildebrand is Executive Director of the “Institute of Behavioral Sciene & Technology” and Full Professor of Marketing Analytics at the University of St. Gallen. He had doctoral and post-doctoral visits at Stanford University, Duke University, and the University of Michigan. His research focuses on leveraging consumer insights from unstructured data (text, voice, image, sensor data) and optimizing consumer-firm interfaces using mobile devices, digital voice assistants, and chatbots. His research has been published in leading academic journals across disciplines (marketing, psychology, and information systems) and he is on the editorial board of the Journal of Consumer Research and the International Journal of Research in Marketing. He is frequently working with corporations across industries from consumer electronics (e.g., Logitech) to automotive (e.g., Audi) and the financial industry (e.g., SwissRe).

Courses taught by this instructor

Course

Description

Instructor

Level

Next course

Location

Course

Description

Instructor

Level

Location

Next course

Voice Analytics for Behavioral Scientists: From Acoustic Features to Conversational AI Agents

The human voice captures what surveys and clicks cannot: Emotion in real-time, cognitive load under pressure, personality through prosody, and authentic reactions before a more conscious reflection. Yet, most behavioral researchers lack the tools to leverage this rich data source. In this 5-day workshop, you’ll master the complete pipeline from audio processing and feature extraction to developing deployable conversational agents for primary data collection. You’ll learn to extract acoustic features that reveal distinct psychological states, transcribe and analyze natural language data, and design voice-based AI systems that can conduct interviews or to develop experimental interventions at scale. What makes this course unique: •Theory meets practice: We cover the fundamentals of speech science and behavioral research foundations while building production-ready interfaces and reproducible analytics pipelines. •Full-stack skills: You will lean the foundations from audio preprocessing to feature extraction to LLM-powered conversational agents all in one course. •Hands-on from day one: We analyze real voice data, build working prototypes, and you will leave with a mini-project tailored to your own research. •Open and responsible: We also cover ethical data practices and how to share your methods transparently with others. This course is ideal for PhD students and researchers in marketing, psychology, economics, communication, HCI, and related fields who want to expand their methodological toolkit and apply voice analytics methods and develop conversational AI agents in their research.
...

...

M

Voice Analytics for Behavioral Scientists: From Acoustic Features to Conversational AI Agents

The human voice captures what surveys and clicks cannot: Emotion in real-time, cognitive load under pressure, personality through prosody, and authentic reactions before a more conscious reflection. Yet, most behavioral researchers lack the tools to leverage this rich data source. In this 5-day workshop, you’ll master the complete pipeline from audio processing and feature extraction to developing deployable conversational agents for primary data collection. You’ll learn to extract acoustic features that reveal distinct psychological states, transcribe and analyze natural language data, and design voice-based AI systems that can conduct interviews or to develop experimental interventions at scale. What makes this course unique: •Theory meets practice: We cover the fundamentals of speech science and behavioral research foundations while building production-ready interfaces and reproducible analytics pipelines. •Full-stack skills: You will lean the foundations from audio preprocessing to feature extraction to LLM-powered conversational agents all in one course. •Hands-on from day one: We analyze real voice data, build working prototypes, and you will leave with a mini-project tailored to your own research. •Open and responsible: We also cover ethical data practices and how to share your methods transparently with others. This course is ideal for PhD students and researchers in marketing, psychology, economics, communication, HCI, and related fields who want to expand their methodological toolkit and apply voice analytics methods and develop conversational AI agents in their research.
...

...