voice
This is a vignette presenting the voice
approach (Zabala 2023) to (Rehder et al. 2022) available audios.
The summarization was made using voice
, an
R library with functions to easily deal with audio.
The summarized dataset via voice
is
available at https://github.com/filipezabala/assinatura_vocal.
path <- 'https://raw.githubusercontent.com/filipezabala/assinatura_vocal/main/Et.csv'
Et <- readr::read_csv(path)
Et
#> # A tibble: 9 × 373
#> subject_id f0_tag_mean f1_tag_mean f2_tag_mean f3_tag_mean f4_tag_mean
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 AN 147. 482. 1593. 2641. 3626.
#> 2 BS 160. 486. 1480. 2443. 3465.
#> 3 EK 177. 520. 1576. 2578. 3493.
#> 4 FP 159. 519. 1640. 2669. 3679.
#> 5 JJ 124. 410. 1554. 2515. 3554.
#> 6 NT 191. 615. 1472. 2503. 3471.
#> 7 SD 191. 480. 1537. 2607. 3509.
#> 8 SR 210. 487. 1441. 2528. 3510.
#> 9 TR 106. 464. 1644. 2585. 3663.
#> # ℹ 367 more variables: f5_tag_mean <dbl>, f6_tag_mean <dbl>,
#> # f7_tag_mean <dbl>, f8_tag_mean <dbl>, zcr1_tag_mean <dbl>,
#> # mhs_tag_mean <dbl>, rms_tag_mean <dbl>, gain_tag_mean <dbl>,
#> # mfcc1_tag_mean <dbl>, mfcc2_tag_mean <dbl>, mfcc3_tag_mean <dbl>,
#> # mfcc4_tag_mean <dbl>, mfcc5_tag_mean <dbl>, mfcc6_tag_mean <dbl>,
#> # mfcc7_tag_mean <dbl>, mfcc8_tag_mean <dbl>, mfcc9_tag_mean <dbl>,
#> # mfcc10_tag_mean <dbl>, mfcc11_tag_mean <dbl>, mfcc12_tag_mean <dbl>, …
Principal Components Analysis (Pearson 1901) applied to dimensionality reduction.
pca3d(pcaE, group = Et$subject_id, show.group.labels = T, show.shadows = F)
#> [1] 0.3844791 0.2789792 0.2131257
#> Creating new device