Lazaro Queiroz

Papers

Total Citations

H-Index

About

Lazaro Queiroz is a researcher at the forefront of human-robot interaction, with a primary focus on speech recognition technologies for robotic systems. His most-cited work, "Comparing Pocketsphinx and Vosk Recognition in human speech decoding" (2021), presented at the IV Brazilian Humanoid Robot Workshop and V Brazilian Workshop on Service Robotics, provides a critical comparative analysis of two leading open-source speech recognition engines. This study, with 3 citations, offers valuable insights into the accuracy and latency trade-offs between Pocketsphinx and Vosk, directly informing the design of more responsive and reliable human-robot communication interfaces. Queiroz’s contributions are particularly significant in the context of service and humanoid robotics, where real-time, accurate speech decoding is essential for natural interaction. His work serves as a practical benchmark for researchers and engineers developing voice-controlled robotic platforms, highlighting the importance of selecting appropriate recognition tools based on specific application requirements. Through this focused investigation, Queiroz has established himself as a key contributor to the advancement of speech-driven robotic systems in Brazil.