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Large language models and emotion AI can detect feelings from voices, faces, and data, and generate video or audio from prompts. We evaluated the emotion detection capabilities of two emotion detection software tools and seven large language models using 70 face images. In this benchmark, GPT o4 Mini High stood out by correctly identifying emotions in 69% of the images.
In addition, we explore ten leading emotion AI tools and share our hands-on insights.
Among the emotion AI tools,
Overall, the results show that current LLMs, particularly GPT-4.1 Mini, can detect emotions from images with moderate success, outperforming most dedicated emotion AI tools in this test.
Read the evaluation criteria section for more details on the benchmark evaluation.
This benchmark tested how well large language models (LLMs) and emotion detection software recognize emotions in images.
Dedicated emotion tools were tested within their specific user interfaces, and the LLMs were tested using their respective API keys or OpenRouter’s universal API keys, depending on availability.
We use a part of the Facial Emotion Detection dataset, which includes a set of labeled images showing different human emotions.1 Each image contained facial expressions representing common emotional states such as happiness, sadness, anger, fear, and surprise.
Nine tools were tested:
Each tool received the same set of images and was asked to identify the dominant emotion shown. The responses were compared with the correct emotion labels. The success rate represents the percentage of images where the tool correctly matched the labeled emotion.
Hume Expression Measurement is an emotion AI tool that helps identify and measure human emotions. It works through a single app and uses four types of data: voice, images, video, and facial expressions. Together, these offer a deeper and more detailed look at how people express emotions.
Real-life experience
This emotion recognition software may not always be 100% accurate, but it captures emotional nuances effectively, especially through speech patterns. However, it’s not perfect. Sometimes, it may not detect basic emotion from vocal bursts. Still, the emotional results often feel realistic and nuanced.
Hume is best for users who want a detailed and responsive look at emotional behavior, not just simple labels like “happy” or “sad.” The web application for the emotion recognition software is extremely user-friendly.
Figure 1. Hume Expression Measurement text analysis for emotions
Figure 2. Hume Expression Measurement text analysis for sentiment
For more information on sentiment analysis, check our sentiment analysis articles.
Hume analyzes speech, images, and videos using several features:
Figure 3. Hume Expression Measurement video analysis for speech prosody
Mangold Observation Studio is a comprehensive platform designed for advanced, sensor-driven research. It brings together many data sources, video, audio, facial expressions, physiological signals, and more, into one synchronized system.
Key features
Visage SDK is a facial emotion recognition software that helps businesses track and analyze faces in real-time. It uses advanced computer vision to understand people’s emotions, age, gender, and identity.
Key features
Applications
Imentiv AI is an emotion detection software that helps users understand how people feel, speak, and behave in video, audio, and text content. It combines artificial intelligence with psychological expertise to analyze human emotion and personality in real time.
Real-life experience:
Imentiv AI helps users analyze emotions from video content. You can upload a full video or focus on a specific frame. The tool looks at facial expressions, voice tone, and the transcript to understand emotional cues.
The analysis seems accurate and covers a wide range of emotional signals. In addition to basic insights, the platform also offers psychological evaluations. These can be scheduled through an appointment system.
Figure 4. Imentiv AI personality trait analysis
Key features
RightFlow is an emotion AI tool that analyzes facial expressions to understand how people feel during their experience with a brand. It helps businesses capture emotions like happiness, anger, fear, or surprise to improve marketing, customer service, and product design.
Key features
Unlike tools focused only on emotion detection, RightFlow combines emotion data with customer counting, demographic tracking, and physical safety features. It’s designed for public spaces, stores, or events where real-time, contact-free analysis matters.
MoodMe’s Face AI Engine is a tool that reads facial expressions to detect emotions in real time. It works directly on the user’s device, with no internet connection or cloud processing needed.
Key features
The Smart Eye Group provides software for analyzing emotion and products with a wearable design. Affectiva AFFDEX 2.0 is a toolkit aimed at analyzing the facial expressions of individuals in real-time. It is designed to analyze facial action units (AU) and head pose to track faces, and detect emotions.
Key features
Hume’s Empathic Voice Interface (EVI) is a speech-to-speech AI system that makes conversations sound more human. It lets users create, clone, and control voices that respond in real-time with emotion and personality.
Real-life experience
In tests, conversations with EVI felt lifelike and engaging. Emotion detection worked well. Users could guide the tone and setting, although this feature didn’t always perform perfectly.
In short, Hume’s Empathic Voice Interface combines fast response, emotional depth, and high control, making conversations with AI sound closer to real human interaction. The web interface of the conversation platform is simple and intuitive to use.
Figure 6. Hume EVI analysis of conversation with AI
Key features
Hume Octave is a voice-based language model that understands the meaning behind words. The company claims that it helps to create conversation with better emotion, rhythm, and tone.
Real-life experience
Octave often found the right voice for a prompt. It helped improve voice descriptions and matched tones well. However, the final voice sometimes sounded flat or artificial, like a weak acting performance. Still, the tool showed strong potential in capturing different speaking styles.
In short, Hume Octave brings meaning to voice. It helps users create more lifelike, expressive speech that fits both the words and the moment and it is very easy to use.
Key features
Revoicer is an AI-powered text-to-speech software with emotion recognition technology that turns written text into realistic voiceovers. It claims to create audio content with emotional tones that sound more human and less emotion AI technology.
Key features
To evaluate each Emotion AI tool fairly, we used the same set of criteria across all platforms. These include:
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We follow ethical norms & our process for objectivity. This research does not feature any customers of AIMultiple.
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