Attractive routes Sound pleasantness of pedestrian walks in urban - PowerPoint PPT Presentation

Attractive routes Sound pleasantness of pedestrian walks in urban environment Catherine Lavandier (Pauline Delaitre – Pierre Aumond)

Sound pleasantness of a soundscape in urban situations Aim of different projects was to propose urban sound quality indicators based on perceptual and acoustic data, collected with different methods Cart_ASUR project (2012-2016): • 13 perceptual data collected with mobile phones in Paris • acoustic data collected through the mobile microphone (dB(A) 1s) • 60 participants (about 30 locations at different periods) • 100 measurements each year per participant • Only 3409 relevant data 2

Sound pleasantness of a soundscape in urban situations GRAFIC project (2013-2017): • perceptual data collected on questionnaires in Paris • acoustic data collected through one mobile sensor (1/3 Oct band-125ms) • georeferenced data for localisation of the measurements 3

Perceptual models of sound pleasantness Cart_ASUR (3409 individual situations) Sound pleasantness = 8.11 – 0.38 * Global loudness – 0.14 * Time ratio of traffic + 0.20 * Time ratio of voices + 0.15 * Time ratio of birds (R²aj=0.34 & r = 0.58 and R²aj=0.80 & r = 0.94 for the mean values) GRAFIC (556 individual situations) Sound pleasantness = 9,70 – 0,47 * Global loudness – 0.21 * Time ratio of traffic + 0.12 * Time ratio of voices + 0.09 * Time ratio of birds (R²aj=0.42 and R²aj=0,90 for the mean values) 4

Acoustic models of sound pleasantness Perceptual Acoustic indicators Acoustic indicators variable (mean values Cart_ASUR (mean values GRAFIC ) L Aeq (0,76) L Aeq (0,73) Global L 50 (0,82) L 50 1Khz (0,85) loudness L 90 (0,71) L 90 (0,72) NNE L>70 (0,75) N 50 (0,80) L Aeq (0,63) L Aeq (0,66) Time ratio of L 50 (0,62) L 50 (0,76) traffic MI L>70 (0,66) L 50 250Hz (0,83) Time ratio of σ ( -0,61) TFSD 500Hz,1s (0,53) voices L A10 – L A90 (-0,61) L A10 – L A90 (NS) Time ratio of L 5 (-0,55) L 10 (-0,46) birds L 10 (-0,53) TFSD 4kHz,125ms (0,81) 5

Acoustic models of sound pleasantness Cart_ASUR (mean values) Sound Pleasantness = 16.92 – 0.15 * L A50 - 0,06 * (L A10 -L A90 ) ( R²aj=60% ) Harmonica = 0.2*(L A95 -30)+0.25*(L Aeq -L A95 ) = - 6 + 0,25 * L Aeq – 0.05 * L A95 Sound Unpleasant = -SP+11= - 5.9 + 0,15 * L A50 +0.06 * L A10 – 0.06 * L A90 GRAFIC (mean values) Sound Pleasant. = 16.70 – 0.24 * L 50 1KHz + 10.9 * TFSD 500Hz + 17.1* TFSD 4KHz ( R²aj=85% ) CENSE (Running project) Sound Pleasant. = ft (L 50 + new indicators for presence of sources extracted from (1/3 Oct band-125ms) in real time with deep learning networks) 6

Sound pleasantness of a pedestrian route dB For each assessment location Additional questions about segment between the assessment locations (~1min ): • perceived pleasant. of the route • strength and velocity of the change of the sound environ. 20 At the middle and the end of the route (~15min ) • perceived pleasantness of the half routes and total route 7

Impact of the direction of the route S [1-2] S [2-3] S [3-4] S [4-5] S [5-6] S [6-7] S [7-8] S [8-9] S [9-10] ∆SP -0,83 -3,26* -0,61 -0,24 2,05 0,43 1,12 0,72 -0,62 SC 3,5 8,7 5,3 5,4 6,3 3,2 6,7 4,6 8,1 S [10-11] S [11-12] S [12-13] S [13-14] S [14-15] S [15-16] S [16-17] S [17-18] S [18-19] ∆SP -1,54 1,35 0,62 1,33 1,63 -0,52 -2,84* 0,10 -1,62 SC 6,5 5,9 5,6 4,9 8,2 2,5 8,8 6,2 8,0 SC = perceived change over 1min GP= Global Pleasantness of the route ∆SP= difference of route pleasantness between directions |∆SP| Recency effect SC Global Pleasantness = 0.85 + 0.44 * P mean + 0.45 * P end ( R²aj=83% ) 8

Impact of the duration of the route Global Pleasantness over 15-minute route is a linear function of the average of the Pleasantness of locations which were assessed during the route. ( r= 0.8 R²=64% ) No recency effect here, - Only 12 mean data - Long term memory ? 9

Pleasantness in a laboratory context • Semi-anechoic room • Immersive video projection • Calibrated sound levels • Professional sound interface • High quality monitoring loudspeakers • Transaural audio restitution Continuous assessment of the sound pleasantness At the end of the route (3-min stimuli ) • perceived pleasantness of the route 10

Construction of the stimuli Controlled audio sequences 30 participants 16 paths from 2 mixed sound environments (park and boulevard) Calibrated binaural microphones Blurred fix image 20 Audiovisual sequences 30 participants 5 paths in both directions Recordings (3 minutes) Video – Mini camera 20 11

Audio controlled sequences only, 3-min long Global Pleasantness = -1.4 + 0.96 * P mean + 0.22 * P end ( R²aj=95% ) ( R²aj=75% if P mean only) 12

Audio visual sequences, 3 minute long Global Pleasantness over 3-minute route is a linear function of the average of the Pleasantness of locations which were assessed during the route. ( Raj²=75% ). No recency effect with complex sequences. 13

Impact of the vision/complexity on the change in sound pleasantness Saliency Change of SP 48.7% Change of SP Saliency 21.5% Δ % = 27.2% Audio only Saliency Change of SP 47.5% Change of SP Saliency 32.8% Δ % = 14.7% Audio-Visual Filipan K. et al., "Auditory sensory saliency as a better predictor of change than sound amplitude in pleasantness assessment of reproduced urban soundscapes", Building and Environment, Vol 148, pp. 730-741, (2018). 14

Summary Sound quality 1-min walk (In Situ) of an attractive GP = 0.85 + 0.44 * P mean + 0.45 * P end ( R²aj=83% ) route Recency effect has 3-min experiment (Laboratory – Audio only) been shown but only GP = -1.4 + 0.96 * P mean + 0.22 * P end ( R²aj=95% ) for short or very controlled paths. Good approximation with More than a 15-min walk (In Situ) the average of the 3 min. (Laboratory – Audio Visual) pleasantness of the GP = P mean ( R²aj=64%-75% ) successive locations. 15

Next steps – Sound Pleasantness of a route 16

Next steps – CENSE Smart City Project • Classical acoustic indicators out of 120 sensors in a 1 Km² area in Lorient • Automatic extraction of time of presence for different types of sound sources • Automatic calculation of Sound Pleasantness Sound Pleasant. = ft (L 50 + new indicators for presence of source extracted from (1/3 Oct band-125ms) in real time with deep learning networks) 17

Next steps – Interactive maps • Interpolation of Sound Pleasantness between sensors (about 50m between each sensor). • Automatic extraction of time of presence for • Natural • Human • Traffic sound sources, shown with dedicated signs on the map. Global Sound Pleasantness of a route ? Improve the models ! 18

Attractive routes Thank you very much for your attention Catherine Lavandier (Pauline Delaitre – Pierre Aumond)