Schreuder et al. Listen, you are writing! FIGURE 7 | Pairwise F -scores between speaker locations. The matrix visualizes the pairwise confusions between an intended location (y axis) and a distracting location (x axis), expressed in F -scores. Lighter colors mean better discrimination. Entries are labeled as l = location neighbor, s = sound neighbor, and fb = front–back symmetric location. on the F -scores of each degrading factor with those pairs with- out degrading factors. After Bonferroni correction, the front–back confusion showed a trend of negative inﬂuence on recognition (p = 0.056). From the pitch neighbors, the highest and lowest pair were most often confused. All this was in line with subjective reporting of the subjects, and gives indicators for future improvements. DISCUSSION A previous ofﬂine study already showed the potential of the AMUSE paradigm (Schreuder et al., 2009, 2010). Now, coupled to a spelling interface, it allowed a majority of healthy subjects to write a full sentence with an average speed of 0.59 char/min on the ﬁrst session, and up to a maximum speed of 1.41 char/min in the second session. To our knowledge, this is the fastest online auditory BCI speller described in literature. For the sake of com- parison, it is important to emphasize once more the conservative nature of the protocol. In the ﬁrst session, 16 out of 21 subjects (or 76%) were able to write a full German sentence. According to Guger et al. (2009) over 90% of people is “able to control a P300-based BCI.” How- ever, as both their tested conditions were overt visual paradigms this may be a too optimistic estimate. The selected BCI paradigms are most prevalent in literature, but may not match fully with the user’s needs and abilities (Brunner et al., 2010; Murguialday et al., 2010; Treder and Blankertz, 2010). Furthermore, for such overt ERP BCI paradigms the learning effect is generally small and average performance is high and consistent over subsequent trials. However, recently Klobassa et al. (2009) showed that for their auditory P3 paradigm the performance increased signiﬁ- cantly after 11 sessions. With subjects performing only up to two sessions, such an increase was not observed here. However, with more training the percentage of people able to use the setup could increase. PERFORMANCE To assess the practical relevance of a BCI speller, the most intu- itive metric is the number of characters that a user can write per minute. However, as this is not uniformly utilized in BCI litera- ture, it makes direct comparison troublesome. For this reason, the ITR as deﬁned by (Schlögl et al., 2007) was reported. The current setup without any dynamic stopping (Session 1) shows ITR values that are en par with the online results of the state-of-the-art audi- tory BCI systems (Sellers and Donchin, 2006; Furdea et al., 2009; Klobassa et al., 2009; Höhne et al., 2010), all of which showed the spelling tree through the visual domain. Owing to the intuitive mapping, this need was eliminated here. With the use of the dynamic stopping method in Session 2, the ITR increased to an average of 5.26 bits/min and a maximum of 7.55 bits/min, which comes close to currently available covert visual BCI systems (Liu et al., 2011; Treder et al., 2011). FRONT–BACK CONFUSION Learning from Schreuder et al. (2010, 2009), the stimuli were opti- mized for better performance. As shown in Figure 7, the number of detrimental factors was limited. However, speakers with the same angle from the frontal and posterior mid-line – speakers 1 and 3 or speakers 4 and 6 in Figure 1 – were confused relatively often. This type of error is well known in hearing research as the front–back confusion and results from an ambiguity in primary interaural differences, ITD in particular (Wightman and Kistler, 1999). It was shown that differentiation in the front–back plane relies on at least two features: (1) spectral cues in the range from 8 to 16 kHz, referred to as the extended high frequency range (EHF; Langendijk and Bronkhorst, 2002) and (2) small head movements (Wightman and Kistler, 1999). Bearing in mind the potential end- user and the short stimulus length, the latter may be out of reach. However, for the ﬁrst feature the noise component of the stimuli used in the current study could be considered suboptimal. Though with aging the sensitivity to this EHF is reduced for a considerable number of people (Fozard and Gordon-Salant, 2001), the upper bound on the noise ﬁlter should be increased to 20 kHz to provide a more optimal range. Furthermore, it is known that for posterior sound sources the intensity of high frequencies is reduced when compared to frontal sources (Blauert, 1983). In this study, the frontal speakers (1 and 6) both had lower frequency ranges in the stimulus complex than their respective confusers in the back (speakers 3 and 4), which may also account for some of the front–back confusion. As shown in (Carlile et al., 1997), most front–back errors occur for locations within 30˚ of the median plane. Unfortunately, the before mentioned speakers in this study fall exactly within this range, which introduces a tertiary source for the found confusion. A simple remedy could be to restrict all speakers to the frontal half, as done ofﬂine before (Schreuder et al., 2010; Belitski et al., 2011). When strictly adhering to the azimuth plane, this leads to a decreased angle between neighboring speakers. For a large number of classes it would be an interesting extension to use the vertical plane as an additional dimension to sustain the number of classes without compromising the spatial resolution of human hearing (Grantham et al., 2003). This is however not without www.frontiersin.org October 2011 | Volume 5 | Article 112 | 9