Audio Features Explorer Tempo, Mood & Recommendations
Decode any Spotify track into 11 quantitative dimensions — danceability, energy, valence, acousticness and more — then surface similar tracks with one call. The toolkit that powers mood-based playlists, fitness apps, sleep aids and recommendation engines.
Analyze a Track
Paste a Spotify track ID or full URL.
Try these examples:
What are Audio Features?
Spotify Audio Features are a set of eleven quantitative descriptors calculated from each track's audio signal. They translate raw waveforms into numerical dimensions that any application can reason about: tempo in beats-per-minute, perceived loudness in decibels, and a family of 0-to-1 scores for danceability, energy, valence, acousticness, instrumentalness, liveness and speechiness. Together they form a compact, reliable fingerprint of how a song sounds and feels — independent of genre, language or release year — making them the foundation of nearly every modern music recommendation engine.
Tempo
Estimated tempo of the track in beats per minute (BPM). Tempo is the speed or pace of a piece, derived from the average duration between beats. A typical pop track sits around 90-130 BPM, while EDM and hardcore can exceed 160. Use tempo for workout playlists, BPM-matched DJ transitions, and rhythm games.
Energy
A 0-to-1 measure of intensity and activity. Energetic tracks feel fast, loud and noisy — death metal scores high, a Bach prelude scores low. Energy is calculated from dynamic range, perceived loudness, timbre, onset rate and general entropy. Pair it with valence to derive mood, or filter for high-energy tracks for HIIT workouts.
Danceability
Describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. Values closer to 1 are highly danceable. Useful for party playlists, fitness apps that match cadence to BPM, and any context where rhythm-driven engagement matters more than melody.
Valence
A 0-to-1 score of musical positiveness. High valence sounds cheerful, euphoric and triumphant; low valence sounds sad, depressed and angry. Combined with energy, valence forms a 2D mood quadrant that powers most modern mood-based recommendation systems and emotional analytics in music therapy and content tagging.
Acousticness
A confidence score from 0 to 1 of whether the track is acoustic. A score of 1 means the model is confident the recording uses primarily acoustic instruments — guitar, piano, strings — with little or no electronic production. Use it to filter for unplugged sessions, classical music, or to deprioritize heavily produced tracks for sleep and study contexts.
Instrumentalness
Predicts whether a track contains no vocals. Values above 0.5 are intended to represent instrumental tracks; 'ooh' and 'ahh' sounds count as instrumental. The closer the value is to 1, the higher the likelihood the track contains no vocal content. Essential for filtering background music for cafes, video soundtracks, and focus playlists.
Liveness
Detects the presence of an audience in the recording. Higher liveness values mean an increased probability the track was performed live. Values above 0.8 strongly suggest a live recording. Useful for filtering studio versus concert versions, surfacing live albums, or excluding audience-heavy versions from clean playlist contexts.
Speechiness
Detects the presence of spoken words in a track. Values above 0.66 indicate tracks made mostly of spoken words like podcasts or audiobooks; 0.33-0.66 indicate music and speech together (rap); below 0.33 typically represent music. Use it to separate podcasts from music or to identify rap and spoken-word tracks.
Loudness
Overall loudness of a track in decibels (dB), averaged across the entire track. Values typically range between -60 and 0 dB. Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Use it for normalization across catalogs, mastering quality assessment, and avoiding sudden volume jumps in cross-fade transitions.
Key & Mode
Key represents the estimated overall tonic of the track using standard pitch class notation (0 = C, 1 = C♯/D♭ … 11 = B). Mode indicates major (1) or minor (0). Together they form the harmonic identity of a song — critical for harmonic mixing in DJ software (Camelot wheel), music education tools, and detecting cover versions across keys.
Time Signature
An estimated overall time signature (meter) of a track. The time signature ranges from 3 to 7, indicating beats per bar (3/4, 4/4, 5/4, 6/4, 7/4). Most popular music is in 4/4. Detecting unusual meters is useful for music theory tools, surfacing prog rock and jazz, and ensuring rhythmic compatibility in playlist transitions.
Use Cases
Mood-Based Playlists
Auto-curate tracks by valence + energy quadrants — happy, sad, calm, energetic.
Fitness Apps
Match BPM to running cadence; surface high-energy tracks for HIIT workouts.
Sleep & Meditation
Filter by low energy + high acousticness for ambient, focus and sleep apps.
Music Match Dating
Compute compatibility scores from users' top-track audio profiles.
Music Therapy
Build evidence-based playlists for anxiety reduction and emotional regulation.
Content Moderation
Flag explicit or speech-heavy tracks via speechiness + content rating.
Recommendation Engines
Power collaborative + content-based filtering with a single API call.
DJ Tools
Auto-suggest harmonic transitions by key, BPM-match next tracks, and detect breakdowns.
Frequently Asked Questions
Where do these scores come from?
Are scores stable across remasters?
Can I batch lookup popularity scores?
How do recommendations work?
What's the difference between tempo and time signature?
Build Smarter Music Apps
Audio features + recommendations + popularity — all on one API key. Free tier available.
Get Your API Key →