{"id":126768,"date":"2026-05-08T02:19:17","date_gmt":"2026-05-08T02:19:17","guid":{"rendered":"https:\/\/www.seeedstudio.com\/blog\/?p=126768"},"modified":"2026-05-09T08:01:44","modified_gmt":"2026-05-09T08:01:44","slug":"from-robots-ears-to-intelligence-how-reachy-mini-understands-the-world-with-a-microphone-array","status":"publish","type":"post","link":"https:\/\/www.seeedstudio.com\/blog\/2026\/05\/08\/from-robots-ears-to-intelligence-how-reachy-mini-understands-the-world-with-a-microphone-array\/","title":{"rendered":"From Robot&#8217;s Ears to Intelligence: How Reachy Mini Understands the World with a Microphone Array"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">How do Robots Really &#8220;Hear Direction&#8221;?<\/h2>\n\n\n\n<figure class=\"wp-block-image size-full\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1003\" height=\"564\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-23.png\" alt=\"\" class=\"wp-image-126903\" srcset=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-23.png 1003w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-23-300x169.png 300w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-23-768x432.png 768w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-23-32x18.png 32w\" sizes=\"(max-width: 1003px) 100vw, 1003px\" \/><\/figure>\n\n\n\n<p>Since the launch of <a href=\"https:\/\/huggingface.co\/reachy-mini\" target=\"_blank\" rel=\"noreferrer noopener\">Reachy Mini<\/a>, we\u2019ve been consistently hearing discussions in the community around a simple but powerful idea: What if robots had &#8220;ears&#8221; like humans?<\/p>\n\n\n\n<p>That means not just microphones for recording sound, but actual spatial hearing, the ability to tell where a sound comes from and react accordingly, without relying on vision.<\/p>\n\n\n\n<p>This question reflects a deeper shift in user expectations. People are no longer asking: &#8220;Can the robot hear?&#8221;<\/p>\n\n\n\n<p>They are asking: &#8220;Can the robot understand space through sound?&#8221;<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Reachy Mini&#8217;s Hearing System: More Than Just Microphones<\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1030\" height=\"773\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-24-1030x773.png\" alt=\"\" class=\"wp-image-126904\" srcset=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-24-1030x773.png 1030w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-24-300x225.png 300w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-24-768x576.png 768w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-24-1536x1152.png 1536w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-24-32x24.png 32w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-24-1024x768.png 1024w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-24.png 2048w\" sizes=\"(max-width: 1030px) 100vw, 1030px\" \/><\/figure>\n\n\n\n<p>Reachy Mini is not just equipped with microphones, it is designed with spatial audio sensing in mind.<\/p>\n\n\n\n<p>\\At the top of its head, Reachy Mini integrates a customized reSpeaker 4-microphone linear array based on <a href=\"https:\/\/www.seeedstudio.com\/ReSpeaker-XVF3800-USB-Mic-Array-p-6488.html\" target=\"_blank\" rel=\"noreferrer noopener\">reSpeaker XMOS XVF3800<\/a>. <\/p>\n\n\n\n<p>*To learn more about the microphone array used in Reachy Mini, check out <a href=\"https:\/\/www.seeedstudio.com\/blog\/reachy-mini-respeaker-voice-ai-robotics\/\" target=\"_blank\" rel=\"noreferrer noopener\">this blog<\/a>. <\/p>\n\n\n\n<p>*To learn more about how to use the reSpeaker inside Reachy Mini for DoA detection, please<a href=\"https:\/\/github.com\/pollen-robotics\/reachy_mini\/blob\/main\/src\/reachy_mini\/media\/audio_doa.py\" target=\"_blank\" rel=\"noreferrer noopener\"> read here<\/a>.)<\/p>\n\n\n\n<p>This setup enables:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Enhanced audio capture within a forward-facing 180\u00b0 field<\/li>\n\n\n\n<li>Improved overall audio pickup quality<\/li>\n\n\n\n<li>Better understanding of voice commands and more responsive interactions<\/li>\n<\/ul>\n\n\n\n<p>This is not a recording device, it is a spatial perception audio sensor.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What Is a Microphone Array?<\/h2>\n\n\n\n<p>A microphone array consists of multiple microphones arranged in a specific geometry. Common configurations on the market include 2-, 4-, 6-, and 8-mic setups, with physical layouts such as linear and circular arrays.<\/p>\n\n\n\n<p>Because of the number of microphones and their spatial arrangement, a microphone array does more than just capture high-quality sound. It enables AI-driven acoustic processing, such as beamforming, automatic gain control (AGC), acoustic echo cancellation (AEC), and dynamic noise suppression.<\/p>\n\n\n\n<p>Most linear arrays are optimized for directional pickup, typically covering a forward-facing 180\u00b0 field. In contrast, circular arrays provide full 360\u00b0 coverage and enhance spatial awareness, enabling Direction of Arrival (DoA) detection.<\/p>\n\n\n\n<p>At a high level, microphone arrays analyze spatial differences between microphones, such as:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Which microphone receives the sound first<\/li>\n\n\n\n<li>Which microphone receives a stronger signal<\/li>\n\n\n\n<li>How waveforms align across channels<\/li>\n<\/ul>\n\n\n\n<p>These differences allow the system to reconstruct where a sound originates in space.<\/p>\n\n\n\n<p>Compared to a single microphone, arrays enable:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Directional awareness<\/li>\n\n\n\n<li>Better noise robustness<\/li>\n\n\n\n<li>Far-field voice capture<\/li>\n\n\n\n<li>Multi-source separation<\/li>\n<\/ul>\n\n\n\n<p>In short, <strong>a microphone array transforms audio from raw sound into spatial information.<\/strong><\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">How Robots &#8220;Hear Direction&#8221;: Core Technologies<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">1. Key Concepts: What They Mean and How They Work<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">DoA (Direction of Arrival)<\/h4>\n\n\n\n<p>DoA estimates the direction (angle) from which a sound arrives. It is the final output of spatial audio processing, used to determine where a speaker or sound source is located.<\/p>\n\n\n\n<p>How it works:<\/p>\n\n\n\n<p>DoA is not measured directly. Instead, it is computed by combining multiple acoustic cues captured across microphones.<\/p>\n\n\n\n<p>To estimate these cues in practice, several well-established algorithms are commonly used:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>GCC-PHAT: the most widely adopted method for estimating time delay between microphones<\/li>\n\n\n\n<li>SRP-PHAT: more computationally intensive, but better suited for multi-source environments<\/li>\n\n\n\n<li>MUSIC: a high-resolution approach that enables precise localization, at the cost of higher complexity<\/li>\n<\/ul>\n\n\n\n<p>The system compares how sound propagates across multiple microphones, and from these spatial differences, it infers the direction of the sound source.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">ITD (Interaural Time Difference)<\/h4>\n\n\n\n<p>ITD is one of the core mechanisms behind DoA. It refers to the tiny time difference between when a sound reaches different microphones. In humans, this is exactly how our ears work \u2014 sound arriving from one side reaches one ear slightly earlier than the other.<\/p>\n\n\n\n<p>How it works:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Assume two microphones are placed at a distance <em>d<\/em><\/li>\n\n\n\n<li>If sound comes from the left \u2192 the left microphone receives it first<\/li>\n\n\n\n<li>The system measures the time delay (\u0394t) between the two signals<\/li>\n\n\n\n<li>Using the speed of sound (~343 m\/s), this delay can be converted into an angle<\/li>\n<\/ul>\n\n\n\n<p>At its core, the principle is simple:<\/p>\n\n\n\n<p><strong>Time difference = Distance difference \/ Speed of sound<\/strong><\/p>\n\n\n\n<p>In practice, systems use techniques like cross-correlation to precisely estimate this delay between signals.<\/p>\n\n\n\n<p>This is the primary cue for low-frequency localization and closely mimics human hearing.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">ILD (Interaural Level Difference)<\/h4>\n\n\n\n<p>ILD refers to the difference in sound intensity (or energy) captured by different microphones.<\/p>\n\n\n\n<p>How it works:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The microphone closer to the source captures a stronger signal<\/li>\n\n\n\n<li>The system compares signal energy across channels<\/li>\n\n\n\n<li>Greater level difference \u2192 sound is more off-center<\/li>\n<\/ul>\n\n\n\n<p>When a sound arrives from one direction:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The microphone closer to the source captures a stronger signal<\/li>\n\n\n\n<li>The farther microphone receives a weaker signal due to attenuation and physical obstruction<\/li>\n<\/ul>\n\n\n\n<p>In human hearing, this is influenced by the \u201chead shadow\u201d effect, where the head blocks part of the sound energy.<\/p>\n\n\n\n<p>ILD is especially effective for high-frequency sounds, where shadowing effects are stronger.<\/p>\n\n\n\n<p>How it\u2019s implemented in microphone arrays:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Capture audio simultaneously across multiple microphones<\/li>\n\n\n\n<li>Calculate signal energy (e.g., RMS or power) for each channel<\/li>\n\n\n\n<li>Compare the intensity differences<\/li>\n\n\n\n<li>Infer the direction based on which side is stronger<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\">Phase Difference<\/h4>\n\n\n\n<p>Phase difference captures how aligned the waveforms are across microphones at a given frequency.<\/p>\n\n\n\n<p>How it works:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Instead of measuring coarse time delay, phase analyzes waveform alignment<\/li>\n\n\n\n<li>Even small shifts in phase can indicate direction<\/li>\n\n\n\n<li>Enables fine-grained, high-resolution localization<\/li>\n<\/ul>\n\n\n\n<p>This is often used in advanced algorithms to refine DoA estimation.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2. How These Concepts Work Together<\/h3>\n\n\n\n<p>These are not independent features, together they form a hierarchy:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>ITD, ILD, and Phase Difference \u2192 provide raw spatial cues<\/li>\n\n\n\n<li>These cues are fused \u2192 to estimate DoA<\/li>\n<\/ul>\n\n\n\n<p>In other words:<\/p>\n\n\n\n<p><strong>Time difference + Level difference + Phase difference \u2192 Direction<\/strong><\/p>\n\n\n\n<p>Each cue has strengths in different conditions:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>ITD \u2192 robust for low frequencies<\/li>\n\n\n\n<li>ILD \u2192 effective for high frequencies<\/li>\n\n\n\n<li>Phase \u2192 improves precision<\/li>\n<\/ul>\n\n\n\n<p>By combining them, systems achieve stable and accurate localization.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3. From Detection to Tracking<\/h3>\n\n\n\n<p>Traditional systems:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Detect sound direction once<\/li>\n\n\n\n<li>Trigger a response<\/li>\n<\/ul>\n\n\n\n<p>Modern systems:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Continuously monitor these cues over time<\/li>\n\n\n\n<li>Track how the sound source moves<\/li>\n<\/ul>\n\n\n\n<p>Key ideas:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Temporal cadence: how often direction is updated<\/li>\n\n\n\n<li>Tracking stability: avoiding jitter in direction estimates<\/li>\n\n\n\n<li>Phase evolution: how phase changes over time to reflect motion<\/li>\n<\/ul>\n\n\n\n<p>This shifts the problem from &#8220;<strong>Where is the sound?<\/strong>&#8221; to &#8220;<strong>How is the sound moving?&#8221;<\/strong><\/p>\n\n\n\n<p>Instead of simply reacting to isolated sound events, robots are beginning to build a continuous understanding of the surrounding acoustic environment.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4. From Microphone Arrays to Spatial Awareness<\/h3>\n\n\n\n<p>All of the above relies on one foundation: microphone arrays.<\/p>\n\n\n\n<p>A single microphone can only capture sound intensity. A microphone array, however, enables:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Measuring time differences (ITD)<\/li>\n\n\n\n<li>Measuring level differences (ILD)<\/li>\n\n\n\n<li>Analyzing phase relationships<\/li>\n<\/ul>\n\n\n\n<p>These capabilities allow the system to compute DoA and track sound sources in space.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">5. What This Means for Robots<\/h3>\n\n\n\n<p>By leveraging these technologies, robots gain a new layer of perception:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Identify where a person is speaking from<\/li>\n\n\n\n<li>Turn toward the speaker<\/li>\n\n\n\n<li>Follow moving voices<\/li>\n\n\n\n<li>Distinguish between multiple sound sources<\/li>\n<\/ul>\n\n\n\n<p><strong>Microphone arrays turn sound into spatial information, enabling robots to move from passive listening to active perception.<\/strong><\/p>\n\n\n\n<p>Different types of robots also require different forms of spatial hearing and voice interaction.<\/p>\n\n\n\n<p>For many robots, the expected direction of incoming sound is relatively predictable. Desktop robots, for example, often receive voice commands from users standing or sitting nearby, typically within a forward-facing or upper-front acoustic field. Interactive robots used in smart retail or customer service scenarios usually rely on face-to-face communication, where directional pickup and speech clarity in front of the robot become especially important.<\/p>\n\n\n\n<p>Humanoid robots, however, require a much stronger sense of spatial awareness. This often means:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Wider pickup coverage, such as full 360\u00b0 sensing<\/li>\n\n\n\n<li>Longer-distance voice capture<\/li>\n\n\n\n<li>More stable tracking of moving speakers in dynamic environments<\/li>\n<\/ul>\n\n\n\n<p>Some advanced designs even place separate microphone arrays at the robot\u2019s left and right \u201cears.\u201d By combining spatial cues from both sides, the system can achieve a listening experience much closer to the human auditory system, enabling more natural sound localization and interaction.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Beyond Localization: Advanced Audio Capabilities<\/h2>\n\n\n\n<p>With microphone arrays like <a href=\"https:\/\/www.seeedstudio.com\/reSpeaker-Flex-XVF3800-Circular-4-p-6737.html\">reSpeaker<\/a>, robots can go beyond direction detection.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Speaker Tracking<\/h4>\n\n\n\n<p>Follow a person as they move and speak.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Beamforming<\/h4>\n\n\n\n<p>Focus on a specific direction while suppressing unwanted sounds from others.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Acoustic Echo Cancellation (AEC)<\/h4>\n\n\n\n<p>Remove the robot\u2019s own voice from the microphone input.<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"reSpeaker Flex Performs AEC and Wake Word Detection\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/tDNBpNKloHU?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\">Noise Suppression (NS)<\/h4>\n\n\n\n<p>Improve speech clarity in real-world environments \u2014 and, most importantly, suppress the internal noise generated by the robot itself.<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"Noise Suppression Test on reSpeaker Flex\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/TQp_8AGE5YA?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<p>These capabilities help transform raw audio into actionable intelligence.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why This Matters for Robotics<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">1. Reduced Dependence on Vision<\/h3>\n\n\n\n<p>Audio perception works even when:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The environment is dark<\/li>\n\n\n\n<li>Objects are partially occluded<\/li>\n\n\n\n<li>Vision systems become computationally expensive<\/li>\n<\/ul>\n\n\n\n<p>Compared to video pipelines, audio processing can often achieve lower latency and lower compute cost.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2. More Natural Interaction<\/h3>\n\n\n\n<p>Humans naturally expect intelligent systems to react toward whoever is speaking.<\/p>\n\n\n\n<p>Spatial hearing allows robots to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Turn toward the active speaker<\/li>\n\n\n\n<li>Maintain conversational awareness<\/li>\n\n\n\n<li>Create interactions that feel significantly more natural<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">3. Multimodal Intelligence (Audio + Vision)<\/h3>\n\n\n\n<p>Audio can guide vision.<\/p>\n\n\n\n<p>Instead of continuously analyzing the entire visual scene, robots can first use sound to determine where attention should go:<\/p>\n\n\n\n<p><strong>Sound \u2192 directs camera attention<\/strong><\/p>\n\n\n\n<p>This creates faster and more efficient perception pipelines, especially in embodied AI systems where compute resources and response time matter.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">A New Direction: From Localization to Sound Field Understanding<\/h2>\n\n\n\n<p>The discussion around robot hearing is also moving beyond simple direction estimation.<\/p>\n\n\n\n<p>Instead of: <strong>delay \u2192 direction<\/strong><\/p>\n\n\n\n<p>Future systems increasingly focus on:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Phase \u2192 orientation<\/li>\n\n\n\n<li>Amplitude \u2192 confidence<\/li>\n\n\n\n<li>Temporal patterns \u2192 stability<\/li>\n<\/ul>\n\n\n\n<p>This leads toward a broader concept:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Sound Field Modeling<\/h3>\n\n\n\n<p>Understanding sound not as isolated events, but as a continuous spatial-temporal structure evolving over time.<\/p>\n\n\n\n<p>Rather than simply detecting \u201cwhere a sound is,\u201d robots begin maintaining a stable acoustic understanding of the environment itself.<\/p>\n\n\n\n<p>This is where robotics audio starts becoming part of a perception system \u2014 not just a sensor stack.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The Role of reSpeaker<\/h2>\n\n\n\n<p>The reSpeaker microphone array provides:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Powerful far-field voice capture<\/li>\n\n\n\n<li>Built-in acoustic algorithms (DoA, AEC, beamforming)<\/li>\n\n\n\n<li>Real-time audio processing capabilities<\/li>\n<\/ul>\n\n\n\n<p>In Reachy Mini, reSpeaker acts as:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The hearing interface<\/li>\n\n\n\n<li>The foundation for spatial audio perception<\/li>\n<\/ul>\n\n\n\n<p>A simple way to think about it:<\/p>\n\n\n\n<p><strong>reSpeaker = the robot&#8217;s &#8220;ears&#8221; + a layer of pre-processing intelligence<\/strong><\/p>\n\n\n\n<p>The microphone array used in Reachy Mini is based on the <a href=\"https:\/\/www.seeedstudio.com\/ReSpeaker-XVF3800-USB-Mic-Array-p-6488.html\" target=\"_blank\" rel=\"noreferrer noopener\">reSpeaker XMOS XVF3800<\/a>. Building on this foundation, we have also introduced a newer microphone array solution designed specifically for <strong>embodied AI<\/strong> applications such as <strong>robotics<\/strong> and <strong>smart signage<\/strong>: <strong><a href=\"https:\/\/www.seeedstudio.com\/reSpeaker-Flex-XVF3800-Circular-4-p-6737.html\" target=\"_blank\" rel=\"noreferrer noopener\">reSpeaker Flex<\/a><\/strong>.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1030\" height=\"898\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-25-1030x898.png\" alt=\"\" class=\"wp-image-126905\" srcset=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-25-1030x898.png 1030w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-25-300x262.png 300w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-25-768x670.png 768w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-25-1536x1339.png 1536w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-25-32x28.png 32w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-25-1024x893.png 1024w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2026\/05\/image-25.png 1732w\" sizes=\"(max-width: 1030px) 100vw, 1030px\" \/><\/figure>\n\n\n\n<p>Compared to traditional integrated microphone arrays, <a href=\"https:\/\/www.seeedstudio.com\/reSpeaker-Flex-XVF3800-Circular-4-p-6737.html\" target=\"_blank\" rel=\"noreferrer noopener\">reSpeaker Flex<\/a> adopts a split-design architecture that <strong>separates the microphone array board from the processing board<\/strong>, making integration significantly easier in space-constrained robotic systems. It is optimized for scenarios requiring directional voice interaction, spatial audio perception, and low-latency edge AI audio processing.<\/p>\n\n\n\n<p><a href=\"https:\/\/www.seeedstudio.com\/reSpeaker-Flex-XVF3800-Circular-4-p-6737.html\" target=\"_blank\" rel=\"noreferrer noopener\">reSpeaker Flex<\/a> also provides:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Flexible hardware integration for robots and embedded AI devices<\/li>\n\n\n\n<li>Enhanced far-field voice capture and real-time acoustic processing<\/li>\n\n\n\n<li>Support for advanced audio algorithms such as DoA, AEC, beamforming, and noise suppression<\/li>\n\n\n\n<li>Open and developer-friendly integration with platforms like ROS2, edge AI systems, and custom voice pipelines<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion: Robots Are Learning to \u201cHear the World\u201d<\/h2>\n\n\n\n<p>We are moving from:<\/p>\n\n\n\n<p><strong>Recording \u2192 Localization \u2192 Tracking \u2192 Understanding<\/strong><\/p>\n\n\n\n<p>The next generation of robots will not just see the world.<\/p>\n\n\n\n<p>They will:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Hear where things are<\/li>\n\n\n\n<li>Understand what matters<\/li>\n\n\n\n<li>Respond naturally in real time<\/li>\n<\/ul>\n\n\n\n<p>And it all starts with something as simple \u2014 and as powerful \u2014 as giving robots the ability to listen like we do.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>How do Robots Really &#8220;Hear Direction&#8221;? Since the launch of Reachy Mini, we\u2019ve been consistently<\/p>\n","protected":false},"author":3659,"featured_media":126908,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_lmt_disableupdate":"","_lmt_disable":"","_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"iawp_total_views":0,"footnotes":""},"categories":[4391,4394,5007,1,4393],"tags":[5229,5228,5227,5284,4959,5232,5395,5410,494,1086,5258,5257],"class_list":["post-126768","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-build","category-deploy","category-feature","category-news","category-tech","tag-aec","tag-agc","tag-doa","tag-embodied-ai","tag-mic-array","tag-microphone-array","tag-reachy-mini","tag-respeaker-flex","tag-robot","tag-robotics","tag-sound-ai","tag-voice-ai"],"yoast_head":"<!-- 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